Food‐based calcium or vitamin D or both for osteoporosis in postmenopausal women

Objectives

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

To assess the benefits and harms of calcium‐ or vitamin D‐rich foods, or both, for preventing osteoporosis in postmenopausal women.

Background

Description of the condition

Osteoporosis is a systemic skeletal disease characterized by low bone density (i.e. 2.5 or more standard deviations below the average value for healthy young women) and compromised microarchitecture of the bone (WHO 1994). Fractures are a common consequence of osteoporosis (particularly at the vertebrae, hip, and/or wrist) and are associated with long‐term health consequences that include reduced mobility, chronic pain, decreased quality of life, and increased risk of mortality (Frost 2013; Gold 2019; Johnell 2006; Leboime 2010; Stanghelle 2019). Osteoporosis represents a significant public health and financial burden, and is estimated to affect more than 200 million people globally and to cause more than 9 million fractures annually (Johnell 2006). The direct healthcare costs of osteoporotic fractures are estimated to be between USD 17.9 and USD 67.3 billion (EUR 56.9 billion) in the United States and Europe alone (Burge 2007; IOF 2021). Notably, the prevalence of the disease and its comorbidities are expected to increase in the coming years owing to longer life expectancies and aging populations (Sarafrazi 2021).

Gender and age are considered biological risk factors for osteoporosis (AHRQ Evidence Report Summary 2001). Women experience disproportionately more bone fragility than men, primarily due to the natural decline in estradiol (a hormone that inhibits bone resorption) that occurs at menopause (AHRQ Evidence Report Summary 2001; Alswat 2017). Individuals older than 65 years also show decreased calcium absorption and reduced production of calcitriol (the active form of vitamin D) (Gallagher 2013). Taken together, postmenopausal women are presumably more susceptible to osteoporosis than any other age or gender subgroups (AACE/ACE 2016; AHRQ Evidence Report Summary 2001). 

Description of the intervention

The identification of effective preventive therapies is crucial to protect the health and well‐being of women after their reproductive years. Current practice guidelines recommend that postmenopausal women should be counselled to maintain adequate dietary intake of calcium (1000 mg to 1200 mg per day) and vitamin D (600 to 800 international units (IU) per day) (AACE/ACE 2016; Ross 2011). Calcium and vitamin D are essential to maintain multiple physiological functions, including bone formation and resorption (Sunyecz 2008). Vitamin D can also be produced endogenously through the skin using ultraviolet radiation, but exposure to ultraviolet radiation differs across populations and may have carcinogenic effects (Wolpowitz 2006). Therefore, diets higher in calcium and vitamin D are commonly recommended in clinical practice (Sunyecz 2008).

Calcium and vitamin D are micronutrients found in naturally occurring or in fortified foods, or both (Sunyecz 2008). Foods that are high in calcium consist of dairy products (e.g. milk and yogurt), fish with bones (e.g. sardines and salmon), and dark‐green vegetables (e.g. kale, broccoli rabe, and turnip greens) (Price 2012; Sunyecz 2008). Two forms of vitamin D can be found in food products: D2 (ergocalciferol) and D3 (cholecalciferol) (Schmid 2013; Slawinska 2017). Vitamin D2 is only synthesized by fungi (e.g. mushrooms), whereas vitamin D3 is largely found in calcium‐rich foods and fortified ready‐to‐eat cereals. It is unclear whether one form of vitamin D results in a greater increase of serum 25‐hydroxyvitamin D concentrations than the other form. However, a meta‐analysis on vitamin D supplements indicated that the D3 form may be more efficacious at raising serum 25‐hydroxyvitamin D concentrations (Tripkovic 2012). Further studies are needed to investigate whether this effect varies by age and gender (Tripkovic 2012).

There is greater emphasis on increasing calcium and vitamin D intake through conventional foods rather than through the use of supplements. This recommendation reflects the growing body of literature that the use of supplements is associated with health risks, including unexpected weight loss, kidney stones, and vascular and tissue calcification (IOM 2011). Although the actual balance of benefits and risks remain unclear in adults (Jackson 2006; Kopecky 2016; Moyer 2013), toxic intakes of calcium and vitamin D are more likely with supplements than conventional foods (IOM 2011). Previous Cochrane Reviews have examined the effects of supplements of calcium and vitamin D in the prevention and treatment of osteoporosis (Avenell 2014; Bolland 2015; Homik 2000). There is also a current review that focuses on calcium and vitamin D for increasing bone mineral density in premenopausal women (Méndez‐Sánchez 2017), a different population group compared to the one in this review. Overall, there is limited understanding of the impact of conventional foods on bone health. This systematic review will consider dietary interventions involving calcium or vitamin D foods alone or in combination with dietary counseling. Interventions may include plant‐ or animal‐based foods with high calcium or vitamin D content, or both.

How the intervention might work

Blood calcium concentrations are tightly regulated by the body due to the role of calcium in cardiovascular health. When the body senses a decrease in calcium concentrations, parathyroid hormone signals the release of calcium ions from the bone matrix into the bloodstream (Boden 1990). Vitamin D also aids in calcium regulation by stimulating synthesis of calcium‐binding receptors in the gut, thereby increasing calcium absorption from the diet (Boden 1990). A calcium or vitamin D deficient diet, or both, weakens bones (resulting in fractures) and reduces calcium absorption (impairing the bone matrix) (Heaney 2006). Interventions involving calcium or vitamin D foods or both are hypothesized to reduce the risk of low bone density and subsequent osteoporosis, because the nutrients are essential to bone health and maintenance (Sunyecz 2008).

Evidence supports that social and emotional support are associated with health benefits and can lead to healthy practices (Reblin 2008). Thus, patient education and counseling are expected to strengthen efforts to incorporate high calcium and vitamin D foods in the diet by providing social, emotional, and informational support.

Why it is important to do this review

Osteoporosis is highly prevalent in postmenopausal women and represents a severe economic burden for this population. Thus, it is essential to identify cost‐effective interventions to prevent this disease. The sole reliance on dietary supplements may not be appropriate for all individuals due to their expense and potential link with poor health outcomes (Anderson 2016). In light of data from the National Health and Nutrition Examination Survey (NHANES) 2003 to 2006, which reported that 57% to 63% of the US population does not use calcium and/or vitamin D supplements (Bailey 2010), it is important to understand whether a diet high in calcium and vitamin D foods reduces the loss of bone mineral density or decreases the risk of fractures and osteoporosis, or both. Furthermore, little is known about whether the duration of the intervention affects the magnitude of the treatment effect. This review will evaluate and summarize the evidence for interventions using calcium‐ or vitamin D‐rich foods, or both, on osteoporosis in postmenopausal women, and will help inform clinical practice guidelines related to bone health.

This review will be conducted according to the guidelines recommended by the Cochrane Musculoskeletal Group Editorial Board (Ghogomu 2014).

Objectives

To assess the benefits and harms of calcium‐ or vitamin D‐rich foods, or both, for preventing osteoporosis in postmenopausal women.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomized controlled trials (RCTs), clinical controlled trials (CCTs), cluster‐randomized trials, and non‐randomized studies with a control or comparison group.

We will also include specific non‐randomized studies (e.g. case‐control, longitudinal cohorts) to complement data that we gather from RCTs, such as baseline risk estimates and overall effectiveness of food‐based calcium and vitamin D intake. Non‐randomized studies can also provide sequential evidence about the longer‐term effects that these food‐based nutrients have on bone health, which may not be observed in RCTs with shorter time frames. The included study designs are based on the Effective Practice and Organization of Care (EPOC) Guidelines.

1. Controlled before‐and‐after studies (CBAs), provided that:

   1. the data in the experimental and control sites were collected in the same time frame, and/or

   2. in the case where studies use a second site as a comparison, the study and control sites were comparable with respect to setting and population.

2. Interrupted time series (ITS) studies (with at least three measurement points before and after intervention), provided the study reported that the intervention occurred at a clearly defined point in time, the study recorded three or more data points at the beginning and at the end of the intervention, and if a repeated measure analysis was performed by investigators. We will exclude ITS studies that ignored secular (trend) changes and that performed a simple t‐test of the pre‐ versus post‐intervention periods without providing justification.

Types of participants

We will include trials that enrol postmenopausal women of any age, where menopause is defined by trial authors (typically defined as 12 months since the cessation of menstruation) (Harlow 2012). Studies including postmenopausal women with or without history of any fracture will be included. Faced with instances where study data on postmenopausal women are combined with premenopausal women, the authors will be contacted for disaggregated data. The study will be excluded from data analysis if no response is received after three consecutive attempts at contact. Within both vertebral and non‐vertebral fractures, women who have had traumatic fractures will be combined with women without a history of fractures. Clinical conditions outside of osteoporosis (e.g. chronic kidney disease) as reported by study authors, or known medications (e.g. aromatase inhibitors) that impact bone metabolism will be considered as confounders.

Types of interventions

We will include RCTs and CCTs that examine calcium or vitamin D foods, or both, versus comparison diets (e.g. usual diet, food counselling only) in this review. Participants in the intervention groups will receive high calcium or vitamin D foods, or both, as defined by the authors. This may include high‐content calcium and/or vitamin D foods determined using food lists developed by the United States Department of Agriculture Dietary Guidelines for Americans 2020 as a reference (USDA 2020). Food counseling in the context of this review is defined as counseling for intake of foods high in calcium or in vitamin D, or both. We will also consider studies in which food‐based calcium or vitamin D or both were compared to non‐food forms of calcium or vitamin D or both (i.e. supplements) groups.

In addition to diet‐only interventions, we will include trials that provide food‐based calcium or vitamin D, or both, as part of a multi‐component intervention (e.g. provision of high calcium and vitamin D foods with counseling and physical activity). The effect of physical activity alone in osteoporosis has been explored by a previous Cochrane Review (Howe 2011) and therefore will not be considered in this review. We will not include studies that examine the effects of calcium and/or vitamin D alone since previous Cochrane Reviews have examined this research question.

The comparisons of interest are.

• Provision of high‐content calcium or vitamin D foods, or both, versus supplement, usual diet, or food counseling only.

• Provision of high‐content calcium or vitamin D foods, or both, and food counseling versus supplement, usual diet, or food counseling only.

• Provision of high calcium and vitamin D foods with counseling and physical activity versus physical activity only.

Types of outcome measures

Major outcomes

1. Incidence of vertebral fractures.

2. Incidence of non‐vertebral fractures (i.e. hip, wrist, forearms).

3. Quality of life.

4. Withdrawals due to adverse events.

5. Serious adverse events (i.e. hospitalizations, events resulting in disability or death).

6. Number of patients experiencing any adverse events.

Minor outcomes

1. Pre‐post changes in bone mineral density (BMD) at the following sites: total hip bone, lumbar spine, combined forearm, total body.

2. Changes in biochemical parameters (e.g. serum 25‐hydroxyvitamin D concentration, alkaline phosphatase, and serum parathyroid hormone).

3. Adherence, as measured by trial authors.

4. Gastrointestinal conditions (self‐reported symptoms including vomiting, abdominal cramps, constipation).

All outcomes will be assessed following a minimum intervention duration of 3 months. Where outcome data allow, we will categorize by period of intervention: 1) calcium or vitamin D foods or both for 3 months; 2) calcium or vitamin D foods or both for greater than 3 months and less than 1 year; and 3) calcium or vitamin D foods or both for greater or equal to 1 year. The 3‐month threshold was selected because this is the minimum period of intervention that is expected to lead to changes in bone formation (Wheater 2013). The 1‐year threshold was selected to observe any sustained changes in bone formation.

BMD must be measured by single‐photon absorptiometry (SPA), dual‐photon absorptiometry (DPA), quantitative computerized tomography (QCT), or dual X‐ray absorptiometry (DXA) at 3 months or more post‐intervention. Fractures must be assessed by X‐ray, computerized tomography, bone scan or magnetic resonance imaging (MRI). Quality of life must be assessed by a validated instrument such as the SF‐36. Study results will be converted to the percentage change in BMD from baseline values (Deeks 2021), where possible. The difference between the percentage of BMD lost in the intervention group and the percentage of BMD lost in the control group will be used as the measure of effect when the data are pooled.

Search methods for identification of studies

Electronic searches

We will perform searches in the following electronic databases:

• Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library (current issue);

• MEDLINE via OVID (1948 to present);

• Embase via Ovid (1974 to current);

• CINAHL (Cumulative Index to Nursing and Allied Health Literature) via EBSCOhost (1982 to present);

• AGRICOLA via OVID (1970 to present);

• Food Science Technology Abstracts via OVID (1969 to present);

• OLDMEDLINE;

• PsycLIT.

The search strategy described in Appendix 1 for MEDLINE will be applied and adopted for similar electronic databases, if appropriate. Databases will be searched from their inception to the present day and will not be restricted by the language of publication. Additionally, we will screen upcoming trials registered at the US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.ClinicalTrials.gov) and the World Health Organization trials portal (www.who.int/ictrp/en/). Studies in the published and unpublished or gray literature will also be examined for this review.

Searching other resources

We will review the reference lists of all primary studies, as well as identified trials for additional references. Relevant manufacturers' websites will be searched for information on trials with a supplement arm that may also include a food‐based intervention arm. Additionally, we will search for errata or retractions from included studies published in full text on PubMed (pubmed.ncbi.nlm.nih.gov) and report the dates that these searches were completed in the review.

Data collection and analysis

Selection of studies

Four review authors, in groups of two (Damian K Francis (DKF) and Annie W Lin (AWL); Beatrice J Leyaro (BJL) and Maduka de Lanerolle Dias (MLD)), will independently screen titles and abstracts that are identified as part of the search. Studies will be coded according to the review inclusion criteria as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. Full‐text reports/publications will be retrieved for studies coded as 'retrieve.' In the same groups of two (DKF and AWL; BJL and MLD), the review authors will independently screen the full‐text reports/publications, identify any studies for inclusion, and record reasons for exclusion of any ineligible studies. The screening process will be managed using Covidence (Covidence). At each step, the four review authors (DKF, AWL, BJL, MLD) will resolve any disagreements through discussion or, if required, through consultation with a third author (DKF or Patricia A Cassano (PAC)). We will identify and exclude duplicates and collate multiple reports of the same study so that each study, rather than each report, is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram (PRISMA Group 2009) and 'Characteristics of excluded studies' table.

Data extraction and management

We will use a data collection form for study characteristics and outcome data, which has been pilot tested on at least one study to be included in the review. Four review authors, in groups of two (AWL and Brittany Y Jarrett (BYJ); BJL and MLD) will conduct duplicate data extraction for relevant study characteristics (i.e. methods, participants, interventions, outcome data). As outlined in the data extraction form (Appendix 2), we will also extract equity data using the PROGRESS guidelines (Mbuagbaw 2017).

We will extract the number of events and sample size per treatment group for dichotomous outcomes, and means, standard deviations, and sample size per treatment group for continuous outcomes. Baseline characteristics data such as calcium and vitamin D intake and blood levels as well as adherence to intervention will also be extracted. We will note in the 'Characteristics of included studies' table when outcome data were not reported in a usable way or when outcome data were transformed or estimated from a study graph, or both. We will resolve any disagreements (i.e. within and between each group of two) by consensus or by involving a third author from the data extraction team (DKF, AWL, BJL, MLD). We will contact the corresponding author of an original report when it is not possible to obtain data from the study graphs, or when there are data extraction questions that cannot be reliably answered using the published data. Medications known to impact bone metabolism, use of anti‐resorptive therapy, body mass index, obesity, diabetes, tobacco smoking, and age over 65 years (Looker 2015) will be considered as confounders.

Two review authors (DKF and AWL) will transfer the outcome data into the Review Manager 5.4 (Review Manager 2020) for analysis. We will double‐check that data have been entered correctly by comparing the data presented in the systematic review with the original study reports.

For RCTs that present pre‐ (i.e. baseline) and post‐intervention values, as well as change data, we will extract the change from the study report. If change has not been reported, then we will calculate change and an appropriate measure of dispersion based on guidance from the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2021). For other study designs, we will extract the post‐intervention values, as appropriate, under the assumption that randomization leads to groups that are similar on pre‐intervention (i.e. baseline) values. We will extract unadjusted values for RCTs and adjusted values for non‐randomized studies of interventions (NRSIs) as per the Cochrane Handbook for Systematic Reviews of Interventions (Reeves 2021). If the studies adjust for different factors, then we will only include unadjusted values in the subsequent meta‐analysis, or we will perform sensitivity analyses to address whether intervention effects vary by covariates included in models. We will extract outcome data that were analyzed in the intention‐to‐treat (ITT) analysis. If these types of outcome data are not available, then we will extract values per protocol or as treated, depending on availability.

Assessment of risk of bias in included studies

Four review authors (DKF, AWL, BJL, MLD) will independently assess the risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021a) and as outlined in Appendix 3. We will assess the risk of bias for included studies using Cochrane risk of bias 2 (RoB 2) tool and ROBINS‐I (Risk Of Bias In Non‐randomized Studies ‐ of Interventions) tool. Disagreements in assessing risk of bias will be resolved by involving a fifth author (PAC). 

We will assess the effect of intention‐treat analysis as well as adhering to intervention as specified in the trial protocol. For 'per‐protocol effect' the following deviations from the intended food‐based calcium intervention will be examined:

• occurrence of non‐protocol interventions (e.g. use of calcium supplement);

• non‐adherence by trial participants to their assigned intervention (concomitant use of calcium supplements);

• failures in implementing the intervention that could affect the outcome (e.g. inadequate vitamin D intake).

Risk of bias assessment will be done for major outcomes; that is, vertebral and non‐vertebral fractures, quality of life, adverse effects, and withdrawals due to adverse effects. We will consider similarity of outcome measure across outcomes such as MRI to detect fractures, and at similar time points of 3 months or more post‐intervention. 

The domains included in RoB 2 are in Additional Table 1. Using signaling questions, judgment in each domain will be expressed as 'low risk of bias', 'some concerns', or 'high risk of bias'. Decisions to arrive at these judgments will be guided by algorithms that map responses to signaling questions to a proposed risk of bias judgment at www.riskofbias.info. The process of managing assessment of risk of bias will be done using the RoB 2 Excel tool available on www.riskofbias.info. 

1. RoB 2.

Bias domain	Issues addressed
Bias arising from the randomization process	Whether: the allocation sequence was random the allocation sequence was adequately concealed baseline differences between intervention groups suggest a problem with the randomization process
Bias due to deviations from intended interventions	Whether: participants were aware of their assigned intervention during the trial carers and people delivering the interventions were aware of participants’ assigned intervention during the trial When the review authors’ interest is in the effect of assignment to intervention:  (if applicable) deviations from the intended intervention arose because of the experimental context (i.e. do not reflect usual practice); and, if so, whether they were unbalanced between groups and likely to have affected the outcome an appropriate analysis was used to estimate the effect of assignment to intervention; and, if not, whether there was potential for a substantial impact on the result When the review authors’ interest is in the effect of adhering to intervention:  (if applicable) important non‐protocol interventions were balanced across intervention groups (if applicable) failures in implementing the intervention could have affected the outcome (if applicable) study participants adhered to the assigned intervention regimen (if applicable) an appropriate analysis was used to estimate the effect of adhering to the intervention
Bias due to missing outcome data	Whether: data for this outcome were available for all, or nearly all, participants randomized (if applicable) there was evidence that the result was not biased by missing outcome data (if applicable) missingness in the outcome was likely to depend on its true value (e.g. the proportions of missing outcome data, or reasons for missing outcome data, differ between intervention groups)
Bias in measurement of the outcome	Whether: the method of measuring the outcome was inappropriate measurement or ascertainment of the outcome could have differed between intervention groups outcome assessors were aware of the intervention received by study participants (if applicable) assessment of the outcome was likely to have been influenced by knowledge of intervention received
Bias in selection of the reported result	Whether: the trial was analyzed in accordance with a pre‐specified plan that was finalized before unblinded outcome data were available for analysis the numerical result being assessed is likely to have been selected, on the basis of the results, from multiple outcome measurements within the outcome domain the numerical result being assessed is likely to have been selected, on the basis of the results, from multiple analyses of the data

A key difference between cluster‐randomized trials and individually‐randomized trials is that participants may be recruited to the trial or otherwise identified for inclusion in the analysis after the clusters have been randomized. This can lead to bias if knowledge of the intervention assigned to a cluster affects recruitment or identification of participants (Higgins 2021b). As such, we will follow guidance for assessing risk of bias for cluster‐randomized trials as outlined by Higgins 2021b.  

For NRSIs with a control or comparator group, including controlled before‐and‐after and follow‐up studies, we will use the validated ROBINS‐I tool to assess risk of bias (Sterne 2016). In each domain, we will assign a judgment of 'low risk of bias', 'moderate risk of bias', 'serious risk of bias', 'critical risk of bias', and 'no information' (Sterne 2016).

We will implement ROBINS‐I (Additional Table 2) in a six‐step process which includes:

2. ROBINS‐I.

Levels	Domains	Domain‐level judgments
Pre‐intervention	Bias due to confounding	Low risk of bias (no confounding expected); moderate risk of bias (confounding expected and controlled for and reliability and validity of important domains are sufficient such that residual confounding is not expected); serious risk of bias (confounding not controlled for or unmeasured and reliability and validity of important domains are low enough such that serious residual confounding is expected); critical risk of bias (confounding not controlled for or measured); no information (no mention of expected confounding)
	Bias in selection of participants	Low risk of bias (eligible participants included and start of follow‐up and start of intervention coincides for each participant); moderate risk of bias (appropriate adjustments were made for selection bias or the start of follow‐up and start of intervention do not coincide for all participants); serious risk of bias (authors do not make appropriate adjustments for moderately strong selection bias and start of follow‐up and start of intervention do not coincide for all participants); critical risk of bias (authors do not make appropriate adjustments for very strong selection bias due to missing follow‐up time and the rate ratio is not constant over time); no information (no information on participant selection or on whether the start of follow‐up and start of the intervention coincide)
At intervention	Bias in classification of intervention	Low risk of bias (intervention and status of intervention are well defined); moderate risk of bias (intervention status is well defined and some aspects of intervention status assignment were determined retrospectively); serious risk of bias (intervention status is not well defined and major aspects of intervention status assignment were determined retrospectively); critical risk of bias (extremely high amount of misclassification of intervention status); no information (no information on intervention and status of intervention)
Post‐intervention	Bias due to deviations from intended intervention	Low risk of bias (deviations from intended intervention reflect usual practice and are unlikely to impact outcome and co‐interventions were balanced); moderate risk of bias (intended intervention deviates from usual practice but is unlikely to impact the outcome, deviations from the intended intervention and an imbalance of co‐interventions across groups are not expected to significantly impact the outcome due to the use of appropriate analyses); serious risk of bias (intended intervention deviates from usual practice and is likely to impact the outcome, deviations from the intended intervention and an imbalance of co‐interventions across groups are expected to significantly impact the outcome due to the absence of appropriate analyses); critical risk of bias (intended intervention deviates significantly from usual practice and is likely to impact the outcome, significant deviations from the intended intervention and an imbalance of co‐interventions across groups are expected to significantly impact the outcome due to the absence of appropriate analyses); no information (no information on deviations from intended intervention)
	Bias due to missing data	Low risk of bias (methods of outcome measurement are comparable across intervention groups, outcome measure is not influenced by participant or outcome assessor knowledge of the intervention received, and error in outcome measurement is not related to intervention status); moderate risk of bias (methods of outcome measurement are comparable across intervention groups, outcome measure is not significantly influenced by participant knowledge of the intervention received, and error in outcome measurement is minimally related to intervention status); serious risk of bias (methods of outcome measurement are not comparable across intervention groups, outcome measure is significantly influenced by participant and outcome assessor knowledge of the intervention received, and error in outcome measurement is related to intervention status); critical risk of bias (methods of outcome measurement are significantly incomparable across intervention groups); no information (no information about methods of outcome assessment)
	Bias in selection of the reported result	Low risk of bias (reported results correspond to all intended outcomes, analyses, and sub‐cohorts); moderate risk of bias (outcome measurements and analyses are clearly defined, there is no indication of both the selection of the reporting from multiple analyses, and the selection of cohorts or subgroups for analyses and reporting is based on the results); serious risk of bias (outcome measurements are not consistently defined, there is indication of both the selection of the reporting from multiple analyses and the selection of cohorts or subgroups for analyses and reporting that is based on the results); critical risk of bias (there is indication of selective reporting of results that are substantially different from the unreported results); no information (not enough information on selection of reported result)

1. specify the research question through consideration of a target trial;

2. specify the outcome and result being assessed;

3. for the specified result, examine how the confounders (e.g. conditions outside osteoporosis and medications affecting bone metabolism) and co‐interventions were addressed;

4. answer signaling questions for the seven bias domains;

5. formulate risk of bias judgments for each of the seven bias domains, informed by answers to the signaling questions;

6. formulate an overall judgment on risk of bias for the outcome and result being assessed.

The ROBINS‐I assesses risk of bias at three levels (using seven domains with appropriate signaling questions), namely:

1. pre‐intervention;

2. at intervention, and

3. post‐intervention.

The review authors will not be blinded to the names of study authors, institutions, journals, and results of included studies. If there are concerns or issues, they will be resolved by discussion or with the opinion of a fifth review author (PAC). Results will be recorded in the relevant 'Characteristics of included studies' tables in Review Manager (Review Manager 2020) and summarized in a risk of bias table or graph.

Assessment of bias in conducting the systematic review

We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

Dichotomous outcomes

We will analyze dichotomous data as risk ratios or as Peto odds ratios when the outcome is considered a rare event (i.e. approximately < 10%) and use 95% confidence intervals (CIs). The number needed to treat (NNTB) will be calculated from the control group event rate and the relative risk using the Visual Rx NNT calculator from population studies (Cates 2016). Both the sample sizes and the number of participants with events will be summed across groups. Absolute events will be presented using the summary of findings tables.

Continuous outcomes

Continuous data will be analyzed as mean difference (MD) or standardized mean difference (SMD), depending on the scale used to measure an outcome, and 95% CIs. We will enter scale data with a consistent direction of effect across studies. When different scales are used to measure the same conceptual outcome (e.g. quality of life), SMDs will be calculated instead with corresponding 95% CIs. SMDs will be back‐translated to a typical scale (e.g. 0 to 10 point scale for quality of life) by multiplying the SMD by a typical among‐person standard deviation (e.g. the standard deviation of the control group at baseline from the most representative trial) as per Chapter 6 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021c). The NNTB for continuous outcomes will be calculated using the Wells calculator.

Unit of analysis issues

Cluster‐randomized trials

We will adjust the clinical trials sample size or standard errors based on the level of randomization using the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021b). We will use an estimate of the intracluster correlation coefficient (ICC) derived from the trial (if available) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021b). If ICCs are not available, we will use ICCs from other sources such as other included studies or similar intervention studies. We will conduct sensitivity analyses based on the ICCs and will consider combining results from the cluster and individually randomized trials to synthesize the relevant information.

Studies with multiple treatment groups

The unit of analysis will be the individual participant. Where multiple trial arms are reported in a single trial, we will include only the arms that meet our eligibility criteria. If two comparisons are combined in the same meta‐analysis, we will halve the comparison group to avoid double‐counting. We will document the presence of multiple treatment groups in the 'Characteristics of included studies' table.

Multiple time points

We will report outcome data at a minimum of 3 months and other time points as reported by study authors during and after the intervention period (i.e. follow‐up). Where studies report outcomes at multiple time points, we will extract data for each time point and pool data from all studies at the same time point. If time points are different across studies and cannot be combined, separate analyses will be presented for each of these time points.

Dealing with missing data

We will contact investigators or study sponsors to obtain missing numerical outcome data where needed (e.g. when a study is identified as abstract only or when data are not available for all participants). In situations where this is not possible, and the missing data are thought to introduce serious bias, we will investigate the impact of including these studies in the overall assessment of results by performing a sensitivity analysis. Any assumptions and imputations to handle missing data will be clearly described and the effect of imputation will be explored (Deeks 2021).

For dichotomous outcomes (e.g. diagnosis of osteoporosis), the diagnosis rate (incidence) will be calculated using the number of patients randomized in the group as the denominator. For continuous outcomes (e.g. mean change in BMD), we will calculate the MD or SMD based on the number of patients analyzed at a particular time point. If the number of patients analyzed is not presented for each time point, then the number of randomized patients in each group at baseline will be used. Where possible, missing standard deviations will be computed from other statistics such as standard errors, CIs or P values, according to the methods recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021c). The potential effect of missing data on conclusions drawn from this review will be described or considered, or both, in the sensitivity analyses.

Assessment of heterogeneity

Clinical and methodological diversity will be assessed in terms of participants, interventions, outcomes, and study characteristics for the included studies to determine whether a meta‐analysis is appropriate. Clinical homogeneity will be examined with respect to participants, interventions, and outcome measures from the data extraction tables. Statistical heterogeneity will be assessed by visual inspection of the forest plot to assess obvious differences in results between the studies and by using the I² and Chi² statistics. We will use the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2021) recommendations to interpret the I² value:

• 0% to 40% might 'not be important';

• 30% to 60% may represent 'moderate' heterogeneity

• 50% to 90% may represent 'substantial' heterogeneity;

• 75% to 100% represents 'considerable' heterogeneity.

As noted in the Cochrane Handbook for Systematic Reviews of Interventions, we will keep in mind that the importance of I² depends on the magnitude and direction of effects and the strength of evidence for heterogeneity. The Chi² test will be interpreted where a P value ≤ 0.10 will indicate evidence of statistical heterogeneity. If we identify substantial heterogeneity, then we will report it and investigate its possible causes though a priori and post hoc subgroup analyses and meta‐regression.

Assessment of reporting biases

We will perform a comparison‐adjusted funnel plot for each outcome (when ≥ 10 studies are available) to explore possible study biases. We will undertake formal statistical tests to investigate funnel plot asymmetry by conducting a linear regression of the effect estimate of the calcium or vitamin D, or both, against the standard error, of the estimate weighted by the inverse of the variance of the intervention (Egger 1997). To assess outcome reporting bias, we will check trial protocols against published reports. For studies published after July 2005, we will screen the clinical trial register at the International Clinical Trials Registry Platform of the World Health Organization (trialsearch.who.int) for the a priori trial protocol. We will evaluate whether selective reporting of outcomes is present.

Data synthesis

RCTs, cluster‐randomized trials, controlled before‐and‐after studies (CBAs)

We will perform analyses using Review Manager 5.4 (Review Manager 2020) and produce forest plots for all analyses. If studies have two or more relevant experimental groups, we will combine these groups to create a single pairwise comparison per recommendations from the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2021). All treatment groups from these trials will be combined into one of the three treatments groups.

1. Provision of high‐content calcium or vitamin D foods, or both. 

2. Provision of high‐content calcium or vitamin D foods, or both, and food counseling. 

3. Provision of high‐content calcium or vitamin D foods, or both, with counseling and physical activity.  

We propose to compare the treatment groups with three different comparator groups: 1) usual diet, 2) supplement (non‐food forms of calcium or vitamin D or both), and 3) food counseling or physical activity only. Groups provided with non‐food forms of calcium and/or vitamin D (i.e. supplements) will be combined and will serve as a comparator group for the treatment groups. Groups that were only provided with food counseling or physical activity will also serve as another comparator group.

Separate meta‐analysis will be conducted for each study design (e.g. RCTs, CBAs) using means, standard deviations, and the number of participants for each outcome in the two groups. Our primary analysis will include studies that are classified at low and some concerns of overall bias. We will also conduct a sensitivity analysis to include all eligible studies regardless of degree of bias. Where study means and standard deviations (SD) are adjusted for different confounders across studies, we will use the unadjusted means and SDs. If an outcome is reported as both categorical and as continuous, these data will be analyzed separately. We will use the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2021) to calculate standard deviation of change scores with available information. For these calculations, we will seek a correlation coefficient for baseline and end of study measurements from the authors or from similar studies that measured the same outcome. We will conduct sensitivity analyses around these variations in the ICCs. Where we are unable to convert reported study data to change scores, these results will not be included in the meta‐analysis but will be reported separately.
 

Data will be pooled using a random‐effects model, specifically the inverse‐variance random‐effects model. Following the principles in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2021), categorical and continuous data will be analyzed separately. We will adjust for clustering as needed in cluster‐randomized trials.

In situations where we cannot combine data in a meta‐analysis, a narrative synthesis will be conducted by summarizing effect estimates according to the Cochrane Handbook for Systematic Reviews of Interventions (McKenzie 2021). We will summarize intervention effect estimates (e.g. risk ratios, odds ratios, hazard ratios with 95% CIs) when appropriate.

Interrupted time series (ITS)

We will calculate relative and absolute mean difference in pre‐ and post‐intervention values. When possible, we will use time series regression to calculate mean change in level and mean change in slope. For discrete outcomes (e.g. osteoporosis diagnosis versus no osteoporosis diagnosis), we will present the relative risk of the outcome for the intervention compared to the control group. We will also calculate the risk difference, which is the absolute difference in the outcome proportions between the groups. We will calculate the number needed to treat to prevent one person from experiencing the outcome.

Subgroup analysis and investigation of heterogeneity

We plan to carry out the following subgroup analyses for vertebral and non‐vertebral fractures.

• Duration of the intervention: 3 to less than 6 months; 6 months to less than 1 year; 1 year or longer.

• Age: 64 years and younger; 65 years and older.

• Proportion of dietary reference intake of calcium and vitamin D provided or recommended by the Institute of Medicine: less than estimated average requirements (EAR); greater or equal to EAR and less than recommended daily allowance (RDA); greater or equal to RDA.

• Baseline calcium and/or vitamin D status following values established by the Institute of Medicine (IOM 2011).

• History of fragility fractures among postmenopausal women.

• Vitamin D insufficiency (< 30 ng/dL) or inadequate intake of calcium using recommended RDA by the Institute of Medicine (IOM 2011).

We will use the formal test for subgroup interactions in Review Manager (Review Manager 2020) and will use caution in the interpretation of subgroup analyses as advised in Section 10 of the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2021). The magnitude of the effects will be compared between the subgroups by means of assessing the overlap of the CIs of the summary estimate.

Sensitivity analysis

To investigate the robustness of the treatment effect of calcium or vitamin D foods, or both, on vertebral and non‐vertebral fractures, the following sensitivity analyses will be conducted.

1. Including all eligible studies, including those with high risk of overall bias.

2. Omitting studies with missing or imputed data.

3. The impact of different ICCs for cluster‐randomized trials on the results (if these are included for RCTs).

Interpreting results and reaching conclusions

We will follow the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2021a; Schünemann 2021b) for interpreting results and will be aware of distinguishing a lack of evidence of effect from a lack of effect. We will base our conclusions only on findings from the quantitative or narrative synthesis of included studies for this review. We will avoid making recommendations for practice, and our 'Implications for research' will suggest priorities for future research and outline the remaining uncertainties in the field.

Summary of findings and assessment of the certainty of the evidence

We will create a summary of findings (SoF) using GRADEpro GDT software (GRADEpro GDT 2021). The template summary tables will include information on the following (Additional Table 3):

3. Summary of findings table template.

Title: Food‐based calcium or vitamin D or both compared with control diets for osteoporosis in postmenopausal women
Patient or population:
Setting:
Intervention:
Comparison:
Outcome Number of participants (studies)	Relative effect (95% CI)	Anticipated absolute effects (95% CI)			Certainty	What happens
		Without INTERVENTION	With INTERVENTION	Difference
Incidence of vertebral fractures	_	_	_	_	_	_
Incidence of non‐vertebral fractures (i.e. hip, wrist, forearms)	_	_	_	_	_	_
Quality of life	_	_	_	_	_	_
Withdrawals due to adverse events	_	_	_	_	_	_
Serious adverse events (i.e. hospitalizations, events resulting in disability or death)	_	_	_	_	_	_
Number of patients experiencing any adverse events	_	_	_	_	_	_
Bone mineral density	_	_	_	_	_	_

• comparisons of interest;

• study design (population, intervention, comparison, outcome (PICO));

• location;

• time point;

• outcome measurements.

In situations where there is RCT and non‐RCT evidence for the outcome, we will report findings from the RCT. Additionally, for each major outcome, we will include the evidence certainty rating, as assessed through the GRADE approach (GRADEpro GDT 2021). We will include the following outcomes in the SoFs table.

1. Vertebral fractures.

2. Non‐vertebral fractures (i.e. hip, wrist, forearms).

3. Quality of life.

4. Withdrawals due to adverse events.

5. Serious adverse events (i.e. hospitalizations, events resulting in disability or death).

6. Number of patients experiencing any adverse events.

7. Bone mineral density.

When assessing the certainty of the evidence, the overall RoB 2 judgment will be used to feed into the GRADE assessment. We will refer to Chapters 8, 14, and 15 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021a; Schünemann 2021a; Schünemann 2021b). The five GRADE considerations (i.e. study limitations, consistency of effect, imprecision, indirectness, and publication bias) will be used to evaluate the certainty of a body of evidence as high, moderate, low, or very low. We will also consider the following criteria in upgrading the certainty of the evidence when appropriate: large effect size, dose‐response gradient, and plausible confounding effect. We will use GRADEpro software to prepare the SoF tables using the version 3 SoF for display (GRADEpro GDT 2021). Through the use of footnotes, we will provide justification for all decisions to down‐ or upgrade the quality of the studies.

Notes

This protocol is based on a template developed by the Cochrane Musculoskeletal Group editorial base.

Appendices

Appendix 1. MEDLINE search strategy

1	exp Postmenopause/	22834
2	(Postmenopaus* or Post‐Menopaus* OR “elderly women”).ti,ab.	56423
3	1 or 2	61168
4	exp Calcium/ or exp Calcium, Dietary/	265700
5	Calcium.ti,ab.	335489
6	4 or 5	460144
7	exp Vitamin D/	52694
8	(“Vitamin D” OR Cholecalciferol* or ERGOCALCIFEROL*).ti,ab.	51684
9	7 or 8	72730
10	6 or 9	505048
11	3 and 10	6038

Appendix 2. Data extraction form

Cochrane Musculoskeletal Group.
Data collection form for intervention reviews: RCTs and non‐RCTs.
Version 3, April 2014.

Notes on using data extraction form

• Be consistent in the order and style you use to describe the information for each report.

• Record any missing information as unclear or not described, to make it clear that the information was not found in the study report(s), not that you forgot to extract it.

• Include any instructions and decision rules on the data collection form, or in an accompanying document. It is important to practice using the form and give training to any other authors using the form.

Review title or ID:

Study ID (surname of first author and year first full report of study was published e.g. Smith 2001):

Report ID:

Report ID of other reports of this study including errata or retractions:

Notes:

General information

Date form completed (dd/mm/yyyy):

Name/ID of person extracting data:

Reference citation:

Study author contact details:

Publication type (e.g. full report, abstract, letter):

Notes:

Study eligibility

Study characteristics	Eligibility criteria (Insert inclusion criteria for each characteristic as defined in the Protocol) 1. Postmenopausal 2. Calcium and/or vitamin D foods 3. Intervention 3 months or more		Eligibility criteria met?			Location in text or source (pg/fig/table/other)
			Yes	No	Unclear
Type of study	Randomized controlled trial		_	_	_	_
	Quasi‐randomized controlled trial		_	_	_	_
	Controlled before‐and‐after study Contemporaneous data collection Comparable control sites At least 2 x intervention and 2 x control clusters		_	_	_	_
	Interrupted time series At least 3 time points before and 3 after the intervention Clearly defined intervention point		_	_	_	_
	Other design (specify):		_	_	_	_
Participants	_		_	_	_	_
Types of intervention	_		_	_	_	_
Types of comparison	_		_	_	_	_
Types of outcome measures	_		_	_	_	_
INCLUDE		EXCLUDE
Reason for exclusion:
Notes:

DO NOT PROCEED IF STUDY EXCLUDED FROM REVIEW

Characteristics of included studies

Methods

Methods	Descriptions as stated in report/paper		Location in text or source (pg/fig/table/other)
Aim of study (e.g. efficacy, equivalence, pragmatic)	_		_
Design (e.g. parallel, cross‐over, non‐RCT)	_		_
Unit of allocation (by individuals, cluster/groups or body parts)	_		_
Start date	_		_
End date	_		_
Duration of participation (from recruitment to last follow‐up)	_		_
Ethical approval needed/obtained for study	Yes No Unclear	_	_
Notes:

Participants

Participants	Description (Include comparative information for each intervention or comparison group if available)		Location in text or source (pg/fig/table/other)
Population description (from which study participants are drawn)	_		_
Setting (including location and social context)	_		_
Inclusion criteria	_		_
Exclusion criteria	_		_
Method of recruitment of participants (e.g. phone, mail, clinic patients)	_		_
Informed consent obtained	Yes No Unclear	_	_
Total number randomized (or total population at start of study for NRCTs)	_		_
Clusters (if applicable, number, type, number of people per cluster)	_		_
Baseline imbalances	_		_
Withdrawals and exclusions (if not provided below by outcome)	_		_
Age	_		_
Sex	_		_
Race/ethnicity	_		_
Severity of illness	_		_
Co‐morbidities	_		_
Other relevant sociodemographics	_		_
Subgroups measure	_		_
Subgroups reported	_		_
Notes:

Intervention groups

(Copy and paste table for each intervention and comparison group)

Intervention Group 1	Description as stated in report/paper	Location in text or source (pg/fig/table/other)
Group name	_	_
Number randomized to group (specify whether number of people or clusters)	_	_
Theoretical basis (include key references)	_	_
Description (include sufficient detail for replication, e.g. content, dose, components)	_	_
Duration of treatment period	_	_
Timing (e.g. frequency, duration of each episode)	_	_
Delivery (e.g. mechanism, medium, intensity, fidelity)	_	_
Providers (e.g. number, profession, training, ethnicity, etc. if relevant)	_	_
Co‐interventions	_	_
Economic information (i.e. intervention cost, changes in other costs as result of intervention)	_	_
Resource requirements (e.g. staff numbers, cold chain, equipment)	_	_
Integrity of delivery	_	_
Compliance	_	_
Notes:

Outcomes

(Copy and paste table for each outcome)

Outcome 1	Description as stated in report/paper		Location in text or source (pg/fig/table/other)
Outcome name	_		_
Time points measured (specify whether from start or end of intervention)	_		_
Time points reported	_		_
Outcome definition (with diagnostic criteria if relevant)	_		_
Person measuring/reporting	_		_
Unit of measurement (if relevant)	_		_
Scales: upper and lower limits (indicate whether high or low score is good)	_		_
Is outcome/tool validated?	Yes No Unclear	_	_
Imputation of missing data (e.g. assumptions made for ITT analysis)	_		_
Assumed risk estimate (e.g. baseline or population risk noted in Background)	_		_
Power (e.g. power and sample size calculation, level of power achieved)	_		_
Notes:

Other

Study funding sources (including role of funders):

Possible conflicts of interest (for study authors):

Notes:

Risk of bias assessment

(See Handbook Chapter 8. Additional domains may be added for non‐randomised studies)

Domain	Risk of bias			Support for judgment (include direct quotes where available with explanatory comments)	Location in text or source (pg/fig/table/other)
	Low	High	Unclear
Random sequence generation (selection bias)	_	_	_	_	_
Allocation concealment (selection bias)	_	_	_	_	_
Blinding of participants and personnel (performance bias)	_	_	_	Outcome group: All/	_
(if separate judgment by outcome(s) required)	_	_	_	Outcome group:	_
Blinding of outcome assessment (detection bias)	_	_	_	Outcome group: All/	_
(if separate judgment by outcome(s) required)	_	_	_	Outcome group:	_
Incomplete outcome data (attrition bias)	_	_	_	Outcome group: All/	_
(if separate judgment by outcome(s) required)	_	_	_	Outcome group:	_
Selective outcome reporting? (reporting bias)	_	_	_	_	_
Other bias	_	_	_	_	_
Notes:

Data and analysis

(Copy and paste the appropriate table for each outcome, including additional tables for each time point and subgroup as required)

For RCT/CCT

Dichotomous outcome

Dichotomous outcome	Description as stated in report/paper					Location in text or source (pg/fig/table/other)
Comparison	_					_
Outcome	_					_
Subgroup	_					_
Time point (specify from start or end of intervention)	_					_
Results	Intervention			Comparison		_
	Number with event	Total in group		Number with event	Total in group
	_	_		_	_
Any other results reported (e.g. odds ratio, risk difference, CI or P value)	_					_
Number of missing participants	_			_		_
Reasons missing	_			_		_
Number of participants moved from other group	_			_		_
Reasons moved	_			_		_
Unit of analysis (by individuals, cluster/groups or body parts)	_					_
Statistical methods used and appropriateness of these (e.g. adjustment for correlation)	_					_
Reanalysis required? (specify, e.g. correlation adjustment)	Yes No Unclear		_			_
Reanalysis possible?	Yes No Unclear		_			_
Reanalyzed results	_					_
Notes:

For RCT/CCT

Continuous outcome

Continuous outcome		Description as stated in report/paper					Location in text or source (pg/fig/table/other)
Comparison		_					_
Outcome		_					_
Subgroup		_					_
Time point (specify from start or end of intervention)		_					_
Post‐intervention or change from baseline?		_					_
Results	Intervention			Comparison			_
	Mean	SD (or other variance, specify)	Number of participants	Mean	SD (or other variance, specify)	Number of participants
	_	_	_	_	_	_
Any other results reported (e.g. mean difference, CI, P value)		_					_
Number of missing participants		_		_			_	_
Reasons missing		_		_			_	_
Number of participants moved from other group		_		_			_	_
Reasons moved		_		_			_	_
Unit of analysis (individuals, cluster/groups or body parts)		_					_
Statistical methods used and appropriateness of these (e.g. adjustment for correlation)		_					_
Reanalysis required? (specify)		Yes No Unclear		_			_
Reanalysis possible?		Yes No Unclear		_			_
Reanalyzed results		_					_
Notes:

For RCT/CCT

Other outcome

Other outcome	Description as stated in report/paper					Location in text or source (pg/fig/table/other)
Comparison	_					_
Outcome	_					_
Subgroup	_					_
Time point (specify from start or end of intervention)	_					_
Number of participants	Intervention			Control		_
	_			_
Results	Intervention result	SE (or other variance)		Control result	SE (or other variance)	_
	_	_		_	_
	Overall results			SE (or other variance)
	_			_
Any other results reported	_					_
Number of missing participants	_			_		_
Reasons missing	_			_		_
Number of participants moved from other group	_			_		_
Reasons moved	_			_		_
Unit of analysis (by individuals, cluster/groups or body parts)	_					_
Statistical methods used and appropriateness of these	_					_
Reanalysis required? (specify)	Yes No Unclear		_			_
Reanalysis possible?	Yes No Unclear		_			_
Reanalyzed results	_					_
Notes:

For controlled before‐and‐after studies (CBA)

CBA	Description as stated in report/paper					Location in text or source (pg/fig/table/other)
Comparison	_					_
Outcome	_					_
Subgroup	_					_
Time point (specify from start or end of intervention)	_					_
Post‐intervention or change from baseline?	_					_
Number of participants	Intervention			Control		_
	_			_
Results	Intervention result	SE (or other variance, specify)		Control result	SE (or other variance, specify)	_
	_	_		_	_
	Overall results			SE (or other variance, specify)
	_			_
Any other results reported	_					_
Number of missing participants	_			_		_
Reasons missing	_			_		_
Number of participants moved from other group	_			_		_
Reasons moved	_			_		_
Unit of analysis (individuals, cluster/groups or body parts)	_					_
Statistical methods used and appropriateness of these	_					_
Reanalysis required? (specify)	Yes No Unclear		_			_
Reanalysis possible?	Yes No Unclear		_			_
Reanalyzed results	_					_
Notes:

For interrupted time series studies (ITS)

ITS	Description as stated in report/paper						Location in text or source (pg/fig/table/other)
Comparison	_						_
Outcome	_						_
Subgroup	_						_
Length of time points measured (e.g. days, months)	_						_
Total period measured	_						_
Number of participants measured	_						_
Number of missing participants	_						_
Reasons missing	_						_
_	Pre‐intervention				Post‐intervention		_
Number of time points measured	_				_		_
Mean value (with variance measure)	_				_		_
Any other results reported	_						_
Unit of analysis (individuals or cluster/groups)	_						_
Statistical methods used and appropriateness of these	_						_
Reanalysis required? (specify)	Yes No Unclear			_			_
Reanalysis possible?	Yes No Unclear			_			_
Individual time point results	_						_
Read from figure?	Yes No	_					_
Reanalyzed results	Change in level		SE		Change in slope	SE	_
	_		_		_	_
Notes:

Other information

Other	Description as stated in report/paper	Location in text or source (pg/fig/table/other)
Key conclusions of study authors	_	_
References to other relevant studies	_	_
Correspondence required for further study information (from whom, what and when)	_
Notes:

Definitions

Assumed risk estimate	An estimate of the risk of an event or average score without the intervention, used in Cochrane summary of findings tables. If a study provides useful estimates of the risk or average score of different subgroups of the population, or an estimate based on a representative observational study, you may wish to collect this information
Bias	A systematic error or deviation in results or inferences from the truth. In studies of the effects of health care, the main types of bias arise from systematic differences in the groups that are compared (selection bias), the care that is provided, exposure to other factors apart from the intervention of interest (performance bias), withdrawals or exclusions of people entered into a study (attrition bias), or how outcomes are assessed (detection bias). Reviews of studies may also be particularly affected by reporting bias, where a biased subset of all the relevant data are available
Change from baseline	A measure for a continuous outcome calculated as the difference between the baseline score and the post‐intervention score
Clusters	A group of participants who have been allocated to the same intervention arm together, as in a cluster‐randomized trial, e.g. a whole family, town, school or patients in a clinic may be allocated to the same intervention rather than separately allocating each individual to different arms
Co‐morbidities	The presence of one or more diseases or conditions other than those of primary interest. In a study looking at treatment for one disease or condition, some of the individuals may have other diseases or conditions that could affect their outcomes
Compliance	Participant behaviour that abides by the recommendations of a doctor, other healthcare provider or study investigator (also called adherence or concordance)
Contemporaneous data collection	When data are collected at the same point(s) in time or covering the same time period for each intervention arm in a study (that is, historical data are not used as a comparison)
Controlled before‐and‐after study (CBA)	A non‐randomized study design where a control population of similar characteristics and performance as the intervention group is identified. Data are collected before and after the intervention in both the control and intervention groups
Exclusions	Participants who were excluded from the study or the analysis by the investigators
Imputation	Assuming a value for a measure where the true value is not available (e.g. assuming last observation carried forward for missing participants)
Integrity of delivery	The degree to which the specified procedures or components of an intervention are delivered as originally planned
Interrupted time series (ITS)	A research design that collects observations at multiple time points before and after an intervention (interruption). The design attempts to detect whether the intervention has had an effect significantly greater than the underlying trend
Post‐intervention	The value of an outcome measured at some time point following the beginning of the intervention (may be during or after the intervention period)
Power	In clinical trials, power is the probability that a trial will obtain a statistically significant result when the true intervention effect is a specified size. For a given size of effect, studies with more participants have greater power. Note that power should not be considered in the risk of bias assessment
Providers	The person or people responsible for delivering an intervention and related care, who may or may not require specific qualifications (e.g. doctors, physiotherapists) or training
Quasi‐randomized controlled trial	A study in which the method of allocating people to intervention arms was not random, but was intended to produce similar groups when used to allocate participants. Quasi‐random methods include: allocation by the person's date of birth, by the day of the week or month of the year, by a person's medical record number, or just allocating every alternate person
Reanalysis	Additional analysis of a study's results by a review author (e.g. to introduce adjustment for correlation that was not done by the study authors)
Report ID	A unique ID code given to a publication or other report of a study by the review author (e.g. first author's name and year of publication). If a study has more than one report (e.g. multiple publications or additional unpublished data) a separate Report ID can be allocated to each to help review authors keep track of the source of extracted data
Sociodemographics	Social and demographic information about a study or its participants, including economic and cultural information, location, age, gender, ethnicity, etc.
Study ID	A unique ID code given to an included or excluded study by the review author (e.g. first author's name and year of publication from the main report of the study). Although a study may have multiple reports or references, it should have one single Study ID to help review authors keep track of all the different sources of information for a study
Theoretical basis	The use of a particular theory (such as theories of human behavior change) to design the components and implementation of an intervention
Unit of allocation	The unit allocated to an intervention arm. In most studies individual participants will be allocated, but in others it may be individual body parts (e.g. different teeth or joints may be allocated separately) or clusters of multiple people
Unit of analysis	The unit used to calculate N in an analysis, and for which the result is reported. This may be the number of individual people, or the number of body parts or clusters of people in the study
Unit of measurement	The unit in which an outcome is measured, e.g. height may be measured in cm or inches; depression may be measured using points on a particular scale
Validation	A process to test and establish that a particular measurement tool or scale is a good measure of that outcome
Withdrawals	Participants who voluntarily withdrew from participation in a study before the completion of outcome measurement

Sources

Cochrane Collaboration Glossary, 2010. Available from www.cochrane.org/glossary

Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al, editor(s). Cochrane Handbook for Systematic Reviews of Interventions Version 6.2 (updated February 2021). Cochrane, 2021. Available from training.cochrane.org/handbook

Last JM, editor(s). A Dictionary of Epidemiology. 4th edition. New York: Oxford University Press, 2001

Schünemann H, Brożek J, Oxman A, editor(s). Handbook for grading the quality of evidence and the strength of recommendations using the GRADE approach (updated October 2013). GRADE Working Group, 2013. Available from gdt.gradepro.org/app/handbook/handbook.html

Contributions of authors

The draft protocol was written by Annie W Lin, Brittany Y Jarrett, Maduka de Lanerolle Dias, and Beatrice J Leyaro.

The draft protocol was finalized by Damian K Francis and Patricia A Cassano.

Sources of support

Internal sources

• No sources of support provided

External sources

• No sources of support provided

Declarations of interest

• Annie W Lin: none known.

• Brittany Y Jarrett: none known.

• Maduka de Lanerolle Dias: none known.

• Beatrice J Leyaro: none known.

• Patricia A Cassano: none known.

• Damian K Francis: none known.

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