This systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (28) and was pre-registered in PROSPERO (ID: CRD42024573534).

We systematically searched PubMed, Embase, Cochrane Library, and Web of Science from their inception to September 7, 2024. The PubMed search used the terms: (“Spirulina” OR “Arthrospira” OR “Spirulina platensis” OR “Spirulina maxima” OR “Arthrospira platensis” OR “Arthrospira maxima”) AND (“overweight” OR “obese” OR “obesity” OR “hypertension” OR “diabetes” OR “metabolic syndrome” OR “body mass index” OR “BMI” OR “body weight” OR “body composition” OR “anthropometric indices” OR “blood pressure” OR “lipids” OR “glucose” OR “fasting blood glucose” OR “FBG” OR “insulin” OR “triglyceride” OR “TG” OR “low density lipoprotein cholesterol” OR “LDL-C” OR “high density lipoprotein cholesterol” OR “HDL-C” OR “total cholesterol” OR “TC”). Search strategies were tailored for other databases by adjusting syntax accordingly. Reference lists of relevant meta-analyses and articles were manually screened to identify additional studies. Two authors (Fu and Zhou) independently reviewed titles and abstracts, with disagreements resolved by a third author (Gu).

Inclusion criteria followed the PICOS framework (Population, Intervention, Comparison, Outcome, Study design):

Population: Adults aged > 18 years with a BMI > 25 kg/m², regardless of gender or comorbidities (e.g., type 2 diabetes, hypertension).

Intervention: Spirulina supplementation (alone or with exercise) for ≥ 2 weeks, delivered as tablets, capsules, or powder.

Comparison: Placebo, control group, exercise alone, or exercise + placebo.

Outcome: At least one measure of metabolic health or body composition, including body weight (BW), body mass index (BMI), body fat percentage (BFP), waist circumference (WC), waist-to-hip ratio (WHR), systolic blood pressure (SBP), diastolic blood pressure (DBP), maximal oxygen uptake (VO2max), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), or insulin (INS).

Study Design: Randomized or non-randomized controlled trials with parallel or crossover designs.

Exclusion criteria encompassed non-human studies, non-English publications, interventions < 2 weeks, those involving other supplements or medications, and studies without metabolic or body composition outcomes. Two authors (Fu and Zhou) independently evaluated full-text eligibility, with disagreements resolved by a third author (Gu).

Two authors (Fu and Zhou) independently extracted data, with accuracy verified by a third author (Gu). Extracted information included: first author, publication year, region, study design, participant characteristics (age, BMI, health status), supplementation protocol (dose, form, duration), exercise protocol (if applicable), and outcome measures (e.g., BW, BMI, TC) with means (M) and standard deviations (SD). All outcomes were standardized to consistent units: BW (kg), BMI (kg/m²), BFP (%), WC (cm), TC (mg/dL), TG (mg/dL), HDL-C (mg/dL), LDL-C (mg/dL), FBG (mg/dL), INS (μIU/mL), SBP (mmHg), DBP (mmHg), and VO2max (mL/kg/min). For missing data, study authors were contacted; studies were excluded if no response was received.

For each group’s pre- and post-intervention data(M, SD, and sample size), the mean difference (MD) was calculated as follows (29):

where M_post is the post-intervention mean and M_pre is the pre-intervention mean. If standard error (SE) was reported instead of SD, it was converted to SD using the formula:

where N is the group sample size. The SD of the mean difference (SD_diff) was then calculated as (29):

where SD_pre is the pre-intervention SD, SD_post is the post-intervention SD, and r is the correlation coefficient between pre- and post-intervention measurements. As the original studies did not report the correlation coefficient (r), we assumed r = 0.8 based on similar studies (30–34).

Risk of bias was evaluated using the Cochrane Risk of Bias 2.0 tool (August 2019) (35), assessing five domains: randomization process, deviations from intended interventions, missing outcome data, outcome measurement, and reported result selection. Two authors (Fu and Zhou) independently assessed each study, with discrepancies resolved by a third author (Gu). Studies were rated as having “low,” “some concerns,” or “high” overall bias.

Evidence quality was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework, categorized as “high,” “moderate,” “low,” or “very low.” Downgrading occurred for risk of bias (“some concerns” or “high” prompted a one-level downgrade), inconsistency (I² > 50% prompted a one-level downgrade), imprecision (statistical power < 80% with unclear effect direction prompted a one-level downgrade), and publication bias [Egger’s test (36) p < 0.05 prompted a one-level downgrade]. GRADE assessments were performed by Fu and verified by Zhou.

Analyses were conducted using R (version 4.2.0) with the meta and metafor packages. Pooled effect sizes were estimated using a random-effects model [DerSimonian-Laird method (37)] and reported as Hedges’ g (g), classified as trivial (< 0.2), small (0.2–0.5), moderate (0.5–0.8), or large (> 0.8) (38). Results included 95% confidence intervals (CI) and prediction intervals (PI, t-distribution-based) to account for heterogeneity (39). Heterogeneity was evaluated with the I² statistic: 0–25% (low), 25–75% (moderate), > 75% (high). Studies with CI not overlapping the pooled effect CI were flagged as outliers. Sensitivity analyses used the leave-one-out method, with statistical power assessed via the metameta package.

Heterogeneity sources were explored through subgroup and regression analyses, requiring ≥ 10 studies for regression and ≥ 5 studies per subgroup (40). Subgroup variables included age (18–44, 45–59, > 60 years), baseline BMI (25–30, > 30 kg/m²), health condition (e.g., type 2 diabetes, hypertension), Spirulina form (tablet, capsule, powder), dose (< 2, 2, 4–10 g/day), and duration (≤ 8, ≥ 12 weeks). Regression analyses employed linear (age, BMI, dose, duration) and cubic polynomial (dose, duration) models, visualized with ggplot2. Publication bias was examined using funnel plots (41) and Egger’s test (36), with p < 0.05 indicating significance. Statistical significance was set at p < 0.05, with 0.05 < p < 0.10 considered a trend.

The database search across PubMed, Embase, Cochrane Library, and Web of Science retrieved 2,855 records. After removing 945 duplicates and excluding 1,889 records that failed to meet inclusion criteria during title and abstract screening, 23 studies (25–27, 42–61) (comprising 28 trials) were included. Of these, 21 trials (25, 26, 42–55, 57–61) examined Spirulina supplementation alone (Spirulina vs. control), while 7 trials (25–27, 42, 56, 59, 60) assessed Spirulina combined with exercise (Spirulina + exercise vs. exercise alone). The selection process is depicted in the PRISMA flow diagram (Figure 1).

A total of 23 studies (28 trials) included 1,035 overweight or obese adults (BMI 25–40 kg/m², aged 21–65 years, 430 males, 270 females, 335 with unreported gender). Of these, 21 trials (867 participants, BMI 25–40 kg/m², aged 26–65 years) evaluated Spirulina supplementation alone, with intervention durations of 2–24 weeks and Spirulina doses of 0.02–10 g/day, administered as tablets, capsules, powders, pills, or extracts. Participants had conditions such as type 2 diabetes, hypertension, metabolic syndrome, treatment-naïve HIV on antiretroviral therapy, or ulcerative colitis. 7 trials (168 participants, BMI 28–33 kg/m², aged 21–62 years) assessed Spirulina combined with exercise, with intervention durations of 4–12 weeks and Spirulina doses of 1–6 g/day, delivered as capsules, tablets, or powders. Exercise regimens included aerobic + resistance training (25, 26), high-intensity interval training (27, 56, 59), weighted yoga (60), or circuit resistance training (42), with participants being overweight or obese without other comorbidities. Control groups received placebo, no intervention, or placebo + exercise. Study details are presented in Tables 1, 2.

Body composition (Figure 2). Spirulina significantly reduced BW compared to controls (N = 8, g = −0.30, 95% CI: −0.53 to −0.08, I² = 15%, p < 0.01, low GRADE). No significant effects were observed for BMI (N = 10, g = −0.25, 95% CI: −0.55 to 0.05, I² = 64%, p = 0.11, very low GRADE), BFP (N = 4, g = 0.06, 95% CI: −0.66 to 0.77, I² = 72%, p = 0.87, low GRADE), WC (N = 4, g = −0.09, 95% CI: −0.35 to 0.18, I² = 0%, p = 0.52, moderate GRADE), or WHR (N = 3, g = 0.10, 95% CI: −0.42 to 0.63, I² = 52%, p = 0.70, low GRADE). Sensitivity analyses showed that excluding Miczke et al. (47) altered the BW pooled result (g = −0.17, 95% CI: −0.40 to 0.06, p = 0.14), and excluding Ngo-Matip et al. (45) altered the BMI pooled result (g = −0.35, 95% CI: −0.62 to −0.08, p = 0.01), though the overall direction of findings remained consistent.

Lipid profile (Figure 2). Spirulina significantly lowered TC (N = 13, g = −0.79, 95% CI: −1.18 to −0.41, I² = 76%, p < 0.01, low GRADE), TG (N = 13, g = −0.64, 95% CI: −1.00 to −0.28, I² = 74%, p < 0.01, low GRADE), and LDL-C (N = 13, g = −0.71, 95% CI: −1.13 to −0.29, I² = 80%, p < 0.01, moderate GRADE), while increasing HDL-C (N = 13, g = 0.53, 95% CI: 0.04 to 1.02, I² = 86%, p = 0.03, very low GRADE). Sensitivity analyses indicated that excluding Mani et al. (43) (g = 0.48, 95% CI: −0.03 to 0.99, p = 0.07), Ghaem Far et al. (52) (g = 0.45, 95% CI: −0.06 to 0.95, p = 0.08), or Supriya et al. (59) (g = 0.50, 95% CI: −0.02 to 1.02, p = 0.06) altered the HDL-C pooled result, but the overall direction remained consistent.

Glucose metabolism (Figure 2). Spirulina showed no significant effect on FBG (N = 9, g = −0.26, 95% CI: −0.75 to 0.23, I² = 80%, p = 0.29, very low GRADE) or INS (N = 4, g = −0.69, 95% CI: −1.62 to 0.24, I² = 84%, p = 0.15, very low GRADE). Sensitivity analyses confirmed that excluding any single study did not alter the overall findings.

Blood pressure (Figure 2). Spirulina significantly reduced DBP (N = 4, g = −0.73, 95% CI: −1.43 to −0.03, I² = 83%, p = 0.04, very low GRADE) and showed a trend toward reducing SBP (N = 4, g = −1.06, 95% CI: −2.23 to 0.10, I² = 93%, p = 0.07, very low GRADE). Sensitivity analyses revealed that excluding Jensen et al. (46) altered the SBP pooled result (g = −1.47, 95% CI: −2.89 to −0.05, p = 0.04), and excluding Jensen et al. (46) (g = −0.85, 95% CI: −1.73 to 0.03, p = 0.06), Miczke et al. (47) (g = −0.61, 95% CI: −1.55 to 0.34, p = 0.21), or Ghaem Far et al. (52) (g = −0.48, 95% CI: −1.20 to 0.25, p = 0.20) altered the DBP pooled result, though the overall direction remained consistent.

Forest plots and sensitivity analyses for all outcomes are presented in Supplementary materials 1–4, 7–10.

Body composition and cardiorespiratory fitness (Figure 3). Compared to placebo + exercise, Spirulina combined with exercise showed no significant effects on BW (N = 4, g = 0.01, 95% CI: −0.40 to 0.42, I² = 0%, p = 0.95, low GRADE), BMI (N = 5, g = −0.54, 95% CI: −1.42 to 0.35, I² = 79%, p = 0.24, very low GRADE), BFP (N = 4, g = −0.12, 95% CI: −0.52 to 0.28, I² = 0%, p = 0.55, low GRADE), or VO2max (N = 3, g = 0.27, 95% CI: −0.20 to 0.74, I² = 0%, p = 0.26, low GRADE). Sensitivity analyses confirmed that excluding any single study did not alter the overall findings.

Lipid profile (Figure 3). Spirulina combined with exercise significantly improved HDL-C (N = 4, g = 1.08, 95% CI: 0.37–1.79, I² = 58%, p < 0.01, low GRADE) and LDL-C (N = 4, g = −0.81, 95% CI: −1.59 to −0.04, I² = 66%, p = 0.04, very low GRADE). No significant effects were observed for TC (N = 4, g = −0.66, 95% CI: −1.67 to 0.34, I² = 80%, p = 0.20, very low GRADE) or TG (N = 4, g = −0.27, 95% CI: −1.20 to 0.65, I² = 77%, p = 0.56, very low GRADE). Sensitivity analyses showed that excluding Hernández-Lepe et al. (25) (g = −0.95, 95% CI: −2.08 to 0.19, p = 0.10), Supriya et al. (59) (g = −0.79, 95% CI: −1.86 to 0.29, p = 0.15), or Bandarrigi et al. (60) (g = −0.48, 95% CI: −1.03 to 0.06, p = 0.08) altered the LDL-C pooled result, though the overall direction remained consistent.

Forest plots and sensitivity analyses for all outcomes are presented in Supplementary materials 5–6, 11–12.

Subgroup analyses (Supplementary materials 13–16) revealed that participant age, BMI, health status, Spirulina form, dose, and intervention duration moderated the effects of Spirulina supplementation on lipid profiles. Notably, greater improvements were observed in participants with type 2 diabetes (T2DM; TC: g = −1.26; TG: g = −1.22; HDL-C: g = 0.67; LDL-C: g = −1.04) and hypertension (HTN; TC: g = −1.18; LDL-C: g = −1.40). Powdered Spirulina (TC: g = −1.61; TG: g = −1.41; HDL-C: g = 1.80; LDL-C: g = −1.62) outperformed tablets or capsules. TC improvements were more pronounced in participants aged 45–59 years (g = −0.98) and at Spirulina doses of 4–10 g/day (g = −1.08). TG improvements were greater at baseline BMI of 25–30 kg/m² (g = −0.98), while LDL-C improvements were optimal at 2 g/day.

Regression analyses (Figure 4) identified relationships between BMI, Spirulina dose, intervention duration, and post-supplementation TG, HDL-C, and LDL-C levels, with no moderating effects observed for other variables (Supplementary materials 17–18). BMI exhibited a linear relationship with TG (R² = 0.48, p < 0.01; Figure 4a), with lower BMI linked to greater TG reductions. Intervention duration showed a non-linear relationship with TG (R² = 0.52, p = 0.04; Figure 4b), HDL-C (R² = 0.68, p < 0.01; Figure 4c), and LDL-C (R² = 0.56, p = 0.02; Figure 4d), with optimal effects at 7–8 weeks (TG: g = −0.91; HDL-C: g = 0.83; LDL-C: g = −1.07) and 24 weeks (TG: g = −1.44; HDL-C: g = 1.87; LDL-C: g = −1.53). Spirulina dose had a non-linear relationship with LDL-C (R² = 0.60, p = 0.02; Figure 4e), with peak effects at 2.8 g (g = −1.14) and 10 g (g = −1.40).

Using the Cochrane Risk of Bias 2.0 assessment, 10 studies (25, 26, 47–53, 58) were rated as low risk, 11 studies (42, 44–46, 52, 54, 56, 57, 59–61) had some concerns, and 2 studies (43, 55) were high risk. Randomization process issues led to high-risk ratings for two studies (43, 55) due to non-random allocation sequences and some concerns for seven studies (44–46, 56, 59–61) due to inadequate allocation concealment. Deviations from intended interventions caused concerns in 10 studies (27, 42–45, 55, 57, 59–61) due to blinding limitations. Incomplete outcome reporting raised concerns in two studies (54, 57). A detailed risk of bias summary, including per-study scores, is provided in Supplementary material 19.

Publication bias for Spirulina’s effects on BMI and lipid profiles was evaluated using funnel plots and Egger’s test (Supplementary Material 20). No significant bias was detected for BMI (p = 0.31), TC (p = 0.32), TG (p = 0.36), HDL-C (p = 0.18), or LDL-C (p = 0.47).

Our findings indicate that Spirulina significantly reduces BW (g = −0.30, ∼2.36 kg), representing approximately 2–3% of initial BW. While this reduction may not meet the 5–10% threshold required for substantial cardiovascular risk reduction in obese patients (80), modest weight loss may still confer meaningful health benefits. A systematic review (81) suggests that weight loss below 5% can still improve cardiovascular, metabolic, and quality-of-life outcomes, indicating Spirulina’s potential clinical relevance for overweight and obese adults, particularly as an adjunct to lifestyle interventions. However, for individuals with severe obesity, additional interventions such as energy restriction or exercise may be necessary to achieve greater weight loss. Spirulina significantly improves lipid profiles, reducing TC (g = −0.79, ∼18.24 mg/dL), TG (g = −0.64, ∼23.50 mg/dL), and LDL-C (g = −0.71, ∼12.44 mg/dL), while increasing HDL-C (g = 0.53, ∼4.20 mg/dL). These changes are clinically significant. Elevated TC levels are positively associated with non-hemorrhagic stroke and total cardiovascular mortality (82). A 10 mg/dL reduction in TG is linked to a 1.6 or 1.4% decrease in mortality, myocardial infarction, and recurrent acute coronary syndrome (83), corresponding to a 3.8 or 3.3% reduction in this study. Each 1 mg/dL increase in HDL-C reduces coronary artery disease risk by 2% in men and 3% in women (84), corresponding to an 8.4% and 12.6% risk reduction for men and women, respectively, in this study. A 10 mg/dL reduction in LDL-C lowers the relative risk of coronary heart disease mortality by 7.2% and coronary events by 7.1% (85), corresponding to reductions of 9 and 8.8% in this study. These findings support Spirulina as a non-pharmacological or adjunctive strategy for dyslipidemia patients at increased cardiovascular risk. Indeed, research (86) demonstrates that Spirulina, as an adjunct to metformin, outperforms metformin alone in long-term blood glucose and lipid control in T2DM patients, without significant adverse effects or hepatic/renal complications. Spirulina significantly reduces DBP (g = −0.73, ∼2.60 mmHg). Clinically, a 2 mmHg reduction in DBP decreases hypertension prevalence by 17%, coronary heart disease risk by 6%, and stroke/transient ischemic attack risk by 15% (87). Thus, our results endorse Spirulina supplementation as a clinically significant non-pharmacological strategy for blood pressure control, though high heterogeneity limits certainty.

The cost-effectiveness of Spirulina supplementation is a key consideration. Commercially available Spirulina is relatively inexpensive (2–3 g daily costs ∼$0.5–2, depending on brand and region) and widely used, with no serious adverse events reported in included studies. Compared to pharmacological interventions (e.g., statins or antihypertensives), Spirulina offers a lower-cost, minimal-side-effect alternative, making it a potentially cost-effective adjunctive therapy, particularly in resource-limited settings. However, it may be insufficient as a standalone treatment for severe metabolic disorders, suggesting its optimal role within comprehensive intervention strategies, including exercise and dietary modifications. Long-term studies are needed to evaluate the sustained cost-effectiveness of Spirulina supplementation.

Future studies should prioritize large-scale, high-quality randomized controlled trials with standardized designs, rigorous implementation, and transparent reporting of randomization, blinding, and raw data to minimize bias. Longer interventions (≥ 12 weeks) are needed to establish the long-term efficacy and safety of Spirulina, alone or combined with exercise. Further research should investigate Spirulina’s effects in specific metabolic disease populations (e.g., T2DM, HTN) to confirm targeted benefits. Optimized exercise protocols should be developed to systematically evaluate Spirulina’s potential to enhance V02max and aerobic capacity. The interactions between Spirulina and exercise-induced metabolic pathways warrant deeper exploration to elucidate the molecular and physiological mechanisms underlying their synergy. Additionally, combining Spirulina with other interventions, such as energy restriction or pharmacotherapy, should be explored to develop comprehensive strategies for managing cardiometabolic health.

This study comprehensively evaluated Spirulina’s effects on multiple cardiometabolic health markers, including body composition, lipid profiles, glucose metabolism, and blood pressure, providing a holistic view of its benefits in overweight and obese adults. It is the first to systematically review the synergistic effects of Spirulina combined with exercise. Subgroup and regression analyses elucidated how participant characteristics (age, BMI, health status) and intervention protocols (form, dose, duration) influence outcomes, offering refined guidance for Spirulina interventions. However, the exclusion of studies lacking key data (e.g., BMI) may have omitted relevant findings. High heterogeneity (I² > 75%) and very low-GRADE certainty for outcomes like glucose metabolism and blood pressure reduce confidence in pooled results, likely due to variability in participant characteristics, Spirulina protocols, or study designs. Most interventions lasted ≤ 12 weeks, limiting insights into Spirulina’s sustained effects. Only seven studies examined Spirulina with exercise, and the diversity of exercise modalities (high-intensity interval training, yoga, resistance training) hindered robust conclusions about synergistic effects.