Effects of oral contraceptives on metabolic parameters in adult premenopausal women: a meta-analysis.

Support for this study came from the Office of the Vice Provost for Research (Vicerrectoría de Investigaciones), School of Medicine, Universidad de los Andes in Bogotá, Colombia. C O Mendivil has received speaker honoraria or has participated in advisory boards for Abbott Laboratories, Amgen, AstraZeneca, Beckman Coulter, Bristol-Myers-Squibb, Boehringer Ingelheim, Café de Colombia, Colmédica, Craveri, Jannsen, LabCare Colombia, Merck S A, Novamed, Novartis, Novo Nordisk, Pfizer, PTC Therapeutics, Rochem Biocare, Sanofi and Sicma Pharma. He has been a consultant to Alpina S A, Bavaria S A, Cuquerella Consulting and Team Foods Colombia.

This meta-analysis was designed and executed according to the guidelines for the preferred reporting items (PRISMA) ( 5 ). The questions to be answered by this meta-analysis were: Among premenopausal women: (i) What are the within-person effects of OCs containing different progestins on plasma lipids? (ii) What are the within-person effects of OCs containing different progestins on other metabolically relevant variables (BMI, FPG, HOMA-IR)? (iii) Do the effects of OCs with different progestins differ in women with PCOS vs without PCOS and (iv) Do the effects of OCs on metabolic variables vary by duration of use? The studies considered for inclusion were those in premenopausal women aged 18 or older, who received oral contraceptives containing chlormadinone, cyproterone, drospirenone, levonorgestrel, desogestrel, dienogest, gestodene or norgestimate, for at least 3 months. The comparator was the baseline value for each outcome variable, namely LDLc, triglycerides (TG), HDLc, HOMA-IR, BMI or fasting plasma glucose (FPG). The search strategy was devised using a combination of keywords and database-specific controlled vocabulary for the concepts of oral contraceptives, lipids and carbohydrates. Additional terminology was added for randomized clinical trials and to eliminate animal studies. Each database, OVID Medline, OVID Embase, LiLACS, and SciELO, was searched from inception, current to July 2020. Please see Supplementary Table 1 (see section on supplementary material given at the end of this article) for a copy of the OVID Medline search. In addition, the reference lists of prior reviews from the Cochrane Database of Systematic Reviews were also reviewed for relevant citations that may not have been picked up through the search strategy. The protocol for this review was registered on PROSPERO (CRD42017078740) and can be accessed at: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=78740. We included all randomized clinical trials of OC reporting mean and standard deviation of plasma LDL cholesterol, HDL cholesterol or triglycerides before and after treatment. The duration of treatment had to be at least 3 months. Only studies in premenopausal women (with or without PCOS) were included. Studies of hormonal replacement therapy, or studies in which OC were used as a treatment for endometriosis were excluded. Trials with incomplete data reporting were also excluded. The inclusion of only randomized clinical trials allowed us to analyze studies with greater methodologic rigor, provision of study intervention and tracking of adherence, all of which improve the ascertainment of exposure status and increase the internal validity of our results. Two individual reviewers examined each article for inclusion according to patient characteristics, design, intervention and outcomes. Any disagreement was resolved through discussion and consensus. One record of each study was included in case of duplicates. We retrieved data from each trial in a de-identified manner, using a standardized form that included estrogen and progestin received, number of participants in each group, relevant demographics and length of follow-up. We extracted for each study group the mean and standard deviation of the baseline and final values for our study outcomes: LDL cholesterol (LDLc), triglycerides, HDLc, homeostasis model assessment-insulin resistance (HOMA-IR), BMI and fasting plasma glucose (FPG). Risk of bias was individually evaluated according to the Cochrane Collaboration’s Risk of Bias Assessment Tool. Each study was considered to have risk of bias (yes or no) in each of six determined categories: allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other bias. We classified studies as follows: If 4–6 domains were ‘yes’: high risk of bias, 2–3 domains: medium risk of bias, 0–1 domains: low risk of bias. We assessed publication bias by visual assessment of the funnel plot asymmetry, and by performing Begg’s and Egger’s tests when there were at least 5 groups for that particular outcome. In cases in which publication bias was likely, we used the trim and fill method (employing the meta trimfill command in STATA) to correct it. A meta-analysis was used to compare changes in metabolic outcomes associated with the use of OC containing different progestins. The effect measure for the meta-analysis was the unstandardized pooled mean difference (pMD) (where mean difference = final mean of outcome − baseline mean of outcome) for each variable of interest within each study group. For our analyses, we grouped OC containing the same progestin, regardless of the dose. We quantified the degree of inter-study heterogeneity with the I 2 statistic and its associated CI. The CI for I 2 in most of our study outcomes did not include zero, so we decided to analyze all endpoints using a random-effects model. Given the heterogeneity between studies in the duration of treatment and study groups, we performed two separate subgroup analyses. First, we performed a comparison by the duration of treatment (less vs more than 12 months), and second, a comparison by the presence of PCOS diagnosis (with PCOS vs without PCOS). In addition, a meta-regression of each outcome vs age and BMI was done for each progestin, adjusting for estrogen dose. Meta-analyses were executed in RevMan, version 5.0, meta-regression analyses in SPSS, version 23, and trim-and-fill analyses in STATA, version 16.

We included in this review 143 study groups from 82 studies, published between 1979 and July 2020 ( Table 1 ). Of the 82 studies, 53 (64.6%) were conducted in Europe, the average group sample size was 22 (Q1−Q3: 15−30) and the duration ranged from 3 to 24 months. A total of 2354 women were included, their average age was 25.1 and their mean BMI 24.7 kg/m 2 . Table 1 Characteristics of study groups included in the meta-analysis. Progestin in OC First author Ref. Country n a Age BMI Follow-up (months) Risk of bias Chlormadinone Vieira (6) Brazil 20 25.0 23.3 12 Medium Chlormadinone Cagnacci (7) Italy 12 28.1 23.1 6 Low Cyproterone Vrbikova (8) Czech Republic 12 25.4 24.4 3 Medium Cyproterone Vexiau (9) France 24 25.0 20.6 12 Medium Cyproterone Vermeulen (10) Belgium 13 – – 6 Low Cyproterone Vermeulen (10) Belgium 17 – – 6 Low Cyproterone Venturoli (11) Italy 20 22.9 22.6 12 Medium Cyproterone Teede (12) Australia 26 33.5 35.8 6 Medium Cyproterone Sabuncu (13) Turkey 14 28.8 37.8 6 Medium Cyproterone Rautio (14) Finland 10 – – 6 Medium Cyproterone Porcile (15) Chile 10 25.0 23.2 24 Low Cyproterone Moran (16) Australia 30 36.0 36.0 6 Medium Cyproterone Miccoli (17) Italy 20 25.0 21.2 6 Low Cyproterone Mhao (18) Iraq 10 – 30.5 3 High Cyproterone Luque-Ramirez (19) Spain 15 23.4 29.2 6 Medium Cyproterone Lemay (20) Canada 7 20.0 33.9 6 High Cyproterone Kahraman (21) Turkey 26 21.0 22.8 12 Medium Cyproterone Hutchison (22) Australia 19 34.1 35.3 6 Medium Cyproterone Hagag (23) Israel 70 21.0 23.5 12 High Cyproterone Fugère (24) Canada 40 22.7 22.1 12 Low Cyproterone Fugère (24) Canada 33 23.2 22.2 12 Low Cyproterone Feng (25) China 41 28.6 27.8 3 Medium Cyproterone Elter (26) Turkey 20 23.5 21.8 4 Low Cyproterone Dardzińska (27) Poland 24 24.9 24.9 4 Medium Cyproterone Cetinkalp (28) Turkey 33 – 24.7 4 High Cyproterone Bilgir (29) Turkey 20 24.3 28.2 3 Medium Cyproterone Leelaphiwat (30) Thailand 16 26.9 23.0 3 Low Cyproterone Behboudi-Gandevani (86) Iran 32 24.2 25.4 3 High Cyproterone Song (87) China 60 27.7 28.6 3 High Desogestrel März (31) Germany 22 – – 3 Low Desogestrel Bertolini (32) Italy 20 – – 6 Low Desogestrel Miccoli (17) Italy 19 26.0 21.1 6 Low Desogestrel Gevers (33) Netherlands 28 – – 12 Low Desogestrel März (34) Germany 11 – – 12 Low Desogestrel Robinson (35) England 17 38.2 20.9 6 Low Desogestrel Steinmetz (36) Germany 23 21.5 21.1 3 Low Desogestrel Petersen (37) Denmark 15 24.0 – 3 Low Desogestrel Porcile (38) Chile 9 – – 24 Medium Desogestrel Porcile (38) Chile 6 – – 24 Medium Desogestrel Porcile (15) Chile 10 22.5 22.5 24 Low Desogestrel Porcile (15) Chile 6 22.4 23.5 24 Low Desogestrel Kauppinen-Mäkelin (39) Finland 15 – – 3 Medium Desogestrel Song (40) China 11 32.2 20.8 3 Medium Desogestrel Song (40) China 11 32.2 20.8 3 Medium Desogestrel Cachrimanidou (41) Sweden 13 24.0 – 12 High Desogestrel Cachrimanidou (41) Sweden 7 24.0 – 12 High Desogestrel Kuhl (42) Germany 16 – – 3 Low Desogestrel Kuhl (42) Germany 16 – – 3 Low Desogestrel Singh (43) USA 23 24.9 – 6 Low Desogestrel van den Ende (44) Netherlands 20 27.5 21.3 3 Low Desogestrel van der Mooren (45) Netherlands 62 26.3 22.5 6 Low Desogestrel Gaspard (46) Belgium 25 21.2 21.9 13 Medium Desogestrel Klipping (47) Netherlands 30 23.7 21.7 6 Medium Desogestrel Banaszewska (48) Poland 48 24.0 22.3 3 Low Desogestrel Cagnacci (49) Italy 20 – 24.1 6 Medium Desogestrel Cagnacci (7) Italy 12 27.8 23 6 Low Desogestrel Kriplani (50) India 29 22.5 26.1 6 Medium Desogestrel Shahnazi (51) Iran 68 30.0 28.7 3 Low Dienogest Wiegratz (52) Germany 25 26.1 21.9 6 Low Dienogest Wiegratz (52) Germany 25 26.1 21.9 6 Low Dienogest Junge (53) Germany 30 28.1 23.2 6 Medium Drospirenone Gaspard (46) Belgium 25 21.5 20.2 13 Medium Drospirenone Klipping (47) Netherlands 29 23.8 21.8 6 Medium Drospirenone Özdemir (54) Turkey 32 22.7 24.3 6 Medium Drospirenone Yildizhan (55) Turkey 72 – 22.9 12 High Drospirenone Battaglia (56) Italy 19 23.4 25.1 6 Low Drospirenone Fruzzetti (57) Italy 16 24.3 24.7 6 Medium Drospirenone Kriplani (50) India 29 22.5 27.6 6 Medium Drospirenone Machado (58) Brazil 39 27.9 22.5 6 Medium Drospirenone Machado (58) Brazil 38 27.7 22.3 6 Medium Drospirenone Mohamed (59) Egypt 245 30.9 25.9 12 Medium Drospirenone Klipping (60) Netherlands 26 24.8 22.5 12 Medium Drospirenone Klipping (60) Netherlands 21 24.4 25.5 12 Medium Drospirenone Klipping (60) Netherlands 28 24.8 22.5 12 Medium Drospirenone Romualdi (61) Italy 15 22.9 22.06 12 Low Drospirenone Romualdi (61) Italy 15 21.9 22.7 12 Low Drospirenone Kahraman (21) Turkey 26 21.5 22.0 12 Medium Drospirenone Orio (62) Italy 50 26.4 27.0 6 Low Gestodene Bertolini (32) Italy 20 – – 6 Low Gestodene Kjaer (63) Denmark 16 24.7 – 6 Low Gestodene Miccoli (17) Italy 18 24.0 20.9 6 Low Gestodene Gevers (33) Netherlands 32 – – 12 Low Gestodene März (31) Germany 11 – – 12 Low Gestodene Robinson (35) England 20 38.1 22.2 6 Low Gestodene Steinmetz (36) Germany 21 20.1 20.3 3 Low Gestodene Petersen (64) Denmark 20 24.5 20.9 6 Low Gestodene Petersen (37) Denmark 19 23.0 – 3 Low Gestodene van der Mooren (45) Netherlands 62 26.1 22.1 6 Low Gestodene Endrikat (65) Germany 35 24.7 22.7 6 Low Gestodene Endrikat (65) Germany 34 25.2 22.6 6 Low Gestodene Merki-Feld (66) Switzerland 8 22.0 – 3 Medium Gestodene Merki-Feld (66) Switzerland 8 20.3 – 3 Medium Gestodene Merki-Feld (67) Switzerland 6 22.8 21.6 3 High Gestodene Merki-Feld (67) Switzerland 6 20.8 24.2 3 High Gestodene Yildizhan (55) Turkey 71 – 22.5 12 High Levonogestrel Larsson-Cohn (68) Sweden 24 27.3 – 6 Low Levonogestrel Larsson-Cohn (68) Sweden 20 23.3 – 6 Low Levonogestrel Larsson-Cohn (68) Sweden 23 25.0 – 6 Low Levonogestrel Larsson-Cohn (68) Sweden 20 23.3 – 6 Low Levonogestrel Larsson-Cohn (68) Sweden 23 25.0 – 6 Low Levonogestrel Larsson-Cohn (69) Sweden 25 – – 6 High Levonogestrel Larsson-Cohn (69) Sweden 25 – – 6 High Levonogestrel Larsson-Cohn (69) Sweden 24 – – 6 High Levonogestrel Larsson-Cohn (69) Sweden 24 – – 6 High Levonogestrel März (34) Germany 22 – – 3 Low Levonogestrel Bertolini (32) Italy 20 – – 6 Low Levonogestrel Boonsiri (70) Thailand 59 23.8 – 12 Medium Levonogestrel Boonsiri (70) Thailand 62 23.7 – 12 Medium Levonogestrel Boonsiri (70) Thailand 66 24.5 – 12 Medium Levonogestrel Kjaer (63) Denmark 17 24.7 – 6 Low Levonogestrel Notelovitz (71) USA 29 25.4 23.6 12 Low Levonogestrel Patsch (72) USA 45 – – 6 Medium Levonogestrel Loke (73) Singapore 21 25.7 20.8 12 Medium Levonogestrel Loke (73) Singapore 24 25.3 21.0 12 Medium Levonogestrel Steinmetz (36) Germany 15 22.5 22.1 3 Low Levonogestrel Janaud (74) France 32 26.1 – 6 Medium Levonogestrel Kauppinen-Mäkelin (39) Finland 15 – – 3 Medium Levonogestrel Song (40) China 12 32.2 20.8 3 Medium Levonogestrel Kakis (75) Canada 8 22.4 22.1 24 Medium Levonogestrel Reisman (76) USA 155 26.8 25.2 4 Medium Levonogestrel Endrikat (77) Germany 23 22.7 22.2 13 Medium Levonogestrel Endrikat (77) Germany 25 24.2 22.5 13 Medium Levonogestrel Merki-Feld (66) Switzerland 8 20.3 – 3 Medium Levonogestrel Merki-Feld (66) Switzerland 8 22.0 – 3 Medium Levonogestrel Merki-Feld (67) Switzerland 6 20.8 24.2 3 High Levonogestrel Merki-Feld (67) Switzerland 6 22.8 21.6 3 High Levonogestrel Wiegratz (52) Germany 25 26.1 21.9 6 Low Levonogestrel Scharnagl (78) Austria 44 27.0 22.3 12 Low Levonogestrel Scharnagl (78) Austria 46 26.0 22.3 12 Low Levonogestrel Skouby (79) Denmark 22 23.5 21.1 12 Medium Levonogestrel Skouby (79) Denmark 27 24.1 21.9 12 Medium Levonogestrel Skouby (80) Denmark 9 22.0 – 6 Medium Levonogestrel Elkind-Hirsch (81) USA 20 29.5 29.5 6 Medium Levonogestrel Ågren (82) Finland 58 29.1 22.3 6 Medium Levonogestrel Junge (53) Germany 28 31.1 22.1 6 Medium Levonogestrel Beasley (83) USA 58 25.0 26.1 3 Low Levonogestrel Beasley (83) USA 51 24.6 26.7 3 Low Levonogestrel Shahnazi (51) Iran 69 28.9 28.5 3 Low Norgestimate Janaud (74) France 34 24.7 – 6 Medium Norgestimate Petersen (64) Denmark 17 23.5 20.3 6 Low Norgestimate Cibula (84) Czech Republic 14 23.2 22.1 6 Medium Norgestimate Essah (85) USA 10 – 32.6 3 Low Norgestimate Hagag (23) Israel 25 22.0 24.0 12 High a n refers to the number of women in the group receiving the progestin of interest. Characteristics of study groups included in the meta-analysis. a n refers to the number of women in the group receiving the progestin of interest. In all but 2 of the included studies (one with dienogest and one with cyproterone), the estrogen present in the OC was ethinyl estradiol. Among the 143 intervention groups included, the progestin received was chlormadinone acetate in 2, cyproterone acetate in 27, desogestrel in 29, dienogest in 3, drospirenone in 17, gestodene in 17, levonorgestrel in 43 and norgestimate in 5. We screened 3470 references through database searching for articles published up to July 2020 ( Fig. 1 ). The searches yielded 948 results from MEDLINE and 2522 from EMBASE and the Cochrane Database of Systematic Reviews. Based on this electronic search, we assessed for duplicates, discarded studies that clearly were not related to the interventions or outcomes of interest and downloaded the titles and abstracts of the remaining records. After abstract review, the number of potentially eligible studies was limited to 152. After procuring the full text of these studies, the complete information for baseline and follow-up measurements of study outcomes was evaluated by at least two independent authors. Seventy studies were excluded because they were reviews or systematic reviews, used a progestin not included in this meta-analysis, had incomplete information on outcomes, were not clinical trials, or failed to meet other eligibility criteria ( Fig. 1 ). Figure 1 PRISMA flowchart of the study. PRISMA flowchart of the study. Use of OC containing chlormadinone (pMD: 9.6 mg/dL; 95% CI: 4.5 to 14.7) was associated with significant increases in HDLc. Similar results were found for cyproterone (pMD: 6.5 mg/dL; 95% CI: 3.1 to 9.9, Fig. 2 ), desogestrel (pMD: 6.8 mg/dL; 95% CI: 5.1 to 8.5, Fig. 3 ), drospirenone (pMD: 7.4 mg/dL; 95% CI: 5.1 to 9.8, Fig. 4 ) and to a lesser extent, gestodene (pMD: 1.5 mg/dL; 95% CI: 0.2 to 2.8) ( Fig. 5 ). In the case of cyproterone, meta-regression analyses showed that older age was significantly correlated with smaller increases in HDLc (standardized beta= −0.58, P  = 0.045). Contrastingly, levonorgestrel use decreased HDLc (pMD: −4.40 mg/dL; 95% CI: −5.67 to −3.13, Fig. 6 ). Studies of norgestimate that reported data on HDLc showed no significant changes ( Fig. 7 ). Figure 2 Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of cyproterone in clinical trials. Figure 3 Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of desogestrel in clinical trials. Figure 4 Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of drospirenone in clinical trials. Figure 5 Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of gestodene in clinical trials. Figure 6 Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of levonorgestrel in clinical trials. Figure 7 Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of norgestimate in clinical trials. Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of cyproterone in clinical trials. Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of desogestrel in clinical trials. Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of drospirenone in clinical trials. Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of gestodene in clinical trials. Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of levonorgestrel in clinical trials. Changes in plasma HDL cholesterol, LDL cholesterol and triglycerides after use of norgestimate in clinical trials. An increase in LDLc was observed for levonorgestrel (pMD: 6.8 mg/dL; 95% CI: 4.3 to 9.3), being significantly larger in long-term (>12 months) studies (pMD: 10.2 mg/dL; 95% CI: 6.2 to 14.2; P  = 0.04 for interaction) ( Table 2 ). Few studies of norgestimate reported LDLc, but these data showed a significant increase (pMD: 11.5 mg/dL; 95% CI: 3.8 to 19.3) ( Fig. 7 ). LDLc increased significantly in women after cyproterone use only in long-term studies (pMD: 11.7 mg/dL; 95% CI: 3.3 to 20.1, P  = 0.003 for interaction) ( Table 2 ). Similarly, LDLc increased only with long-term use for desogestrel (pMD: 22.3 mg/dL; 95% CI: 5.7 to 38.9; P  = 0.01 for interaction) and drospirenone (pMD: 6.3 mg/dL; 95% CI: 0.6 to 12.0; P  = 0.04 for interaction) ( Table 2 ). By contrast, use of dienogest-containing OC was associated with a significant reduction in LDLc (pMD: −7.7 mg/dL; 95% CI: −14.9 to −0.5). Table 2 Changes in metabolic outcomes after use of oral contraceptives containing different progestins, by study duration. Outcome Subgroup (months) N studies (participants) pMD (95% CI) I 2 P -value for difference between subgroups P -value for heterogeneity Cyproterone BMI <12 14 (300) −0.13 (−0.45, 0.19) 0 0.35 0.66 ≥12 2 (50) 0.23 (−0.46, 0.92) 0 0.84 Glucose <12 11 (233) −1.63 (−3.11, −0.16) 11 0.64 0.34 ≥12 2 (50) −3.11 (−9.09, 2.87) 97 <0.0001 TG <12 18 (347) 23.7 (15.6, 31.9) 80 0.49 <0.0001 ≥12 6 (213) 32.6 (8.9, 56.2) 96 <0.0001 HDL <12 18 (347) 6.87 (2.64, 11.1) 93 0.94 <0.0001 ≥12 4 (133) 6.55 (−0.56, 13.7) 81 0.0002 LDL <12 18 (347) −3.07 (−7.83, 1.69) 66 0.002 <0.0001 ≥12 5 (179) 11.7 (3.34, 20.2) 61 0.04 HOMA <12 9 (216) −0.32 (−0.85, 0.22) 97 0.64 <0.0001 ≥12 1 (26) −0.55 (−1.39, 0.29) NA NA Chlormadinone BMI <12 1 (12) 0.20 (−2.45, 2.85) NA 0.87 NA ≥12 1 (20) 0.50 (−2.10, 3.10) NA NA Glucose <12 1 (12) 0 (−4.04, 5.04) NA 0.28 NA ≥12 1 (20) −4.20 (−10.01, 1.61) NA NA TG <12 1 (12) 23.0 (5.80, 40.2) NA 0.12 NA ≥12 1 (20) 56.7 (17.6, 95.8) NA NA HDL <12 1 (12) 12.3 (1.01, 23.6) NA 0.60 NA ≥12 1 (20) 8.90 (3.22, 14.6) NA NA LDL <12 1 (12) −7.70 (−32.9, 17.5) NA 0.53 NA ≥12 1 (20) −0.76 (−13.7, 12.1) NA NA HOMA <12 – NA NA – NA ≥12 – NA NA NA Desogestrel BMI <12 6 (196) 0.11 (−0.45, 0.67) 0 0.16 0.79 ≥12 2 (15) 2.20 (−0.67, 5.07) 0 0.99 Glucose <12 9 (281) 1.53 (−0.56, 3.61) 58 – NA ≥12 – NA NA NA TG <12 18 (451) 25.9 (18.6, 33.2) 74 0.40 <0.0001 ≥12 4 (86) 33.1 (18.0, 48.2) 71 0.008 HDL <12 19 (481) 6.69 (4.94, 8.45) 33 0.73 0.08 ≥12 7 (102) 7.63 (2.72, 12.5) 52 0.05 LDL <12 18 (465) 0.19 (−4.37, 4.75) 58 0.001 ≥12 9 (117) 22.3 (5.66, 38.9) 80 <0.0001 HOMA <12 – NA NA – NA ≥12 – NA NA NA Drospirenone BMI <12 5 (146) −0.07 (−0.87, 0.73) 0 0.25 0.96 ≥12 4 (128) −0.69 (−1.04, −0.16) 0 0.58 Glucose <12 7 (223) 0.27 (−2.36, 2.90) 76 0.37 0.0003 ≥12 2 (271) 4.71 (−4.60, 14.01) 98 <0.0001 TG <12 6 (173) 24.0 (12.4, 35.6) 61 0.06 0.03 ≥12 9 (479) 38.9 (28.4, 49.4) 92 <0.0001 HDL <12 8 (252) 7.91 (4.11, 11.7) 67 0.78 0.003 ≥12 9 (479) 7.21 (4.12, 10.3) 82 <0.0001 LDL <12 8 (252) −2.96 (−9.71, 3.80) 62 0.04 0.01 ≥12 9 (479) 6.30 (0.56, 12.0) 84 <0.0001 HOMA <12 5 (146) −0.16 (−0.61, 0.28) 60 0.64 0.04 ≥12 6 (172) 0.10 (−0.91, 1.11) NA NA Gestodene BMI <12 2 (38) 0.56 (−0.50, 1.63) 0 0.47 0.64 ≥12 1 (71) 0.10 (−0.56, 0.76) NA NA Glucose <12 – NA NA – NA ≥12 – NA NA NA TG <12 12 (281) 25.7 (21.1, 30.3) 0 0.79 0.69 ≥12 3 (114) 28.0 (11.2, 44. 9) 77 0.01 HDL <12 13 (273) 1.39 (−0.03, 2.81) 2 0.53 0.43 ≥12 3 (114) 2.80 (−1.39, 7.00) 42 0.18 LDL <12 9 (245) −3.24 (−6.88, 0.40) 2 0.37 0.42 ≥12 3 (359) −1.01 (−4.20, 2.18) 0 0.64 HOMA <12 – NA NA – NA ≥12 – NA NA NA Levonorgestrel BMI <12 – NA NA – NA ≥12 – NA NA NA Glucose <12 5 (199) −3.0 (−11.1, 5.09) 87 0.35 <0.0001 ≥12 4 (296) −8.16 (−15.3, −0.99) 88 <0.0001 TG <12 25 (650) 13.7 (9.42, 17.9) 41 0.26 0.02 ≥12 13 (456) 9.02 (2.06, 16.0) 64 0.0008 HDL <12 28 (707) −4.19 (−5.73, −2.66) 58 0.59 <0.0001 ≥12 11 (407) −4.94 (−7.18, −2.70) 31 0.15 LDL <12 16 (496) 5.08 (2.42, 7.75) 0 0.04 0.49 ≥12 13 (456) 10.2 (6.15, 14.2) 21 0.23 HOMA <12 – NA NA – NA ≥12 – NA NA NA Norgestimate BMI <12 – NA NA – NA ≥12 – NA NA NA Glucose <12 – NA NA – NA ≥12 – NA NA NA TG <12 5 (98) 36.3 (28.3, 44.2) 56 0.04 0.06 ≥12 1 (25) 27.3 (23.9, 30.7) NA NA HDL <12 – NA NA – NA ≥12 – NA NA NA LDL <12 4 (81) 9.02 (5.73, 12.3) 0 0.0002 0.86 ≥12 1 (25) 17.8 (14.6, 20.8) NA NA HOMA <12 – NA NA – NA ≥12 – NA NA NA NA, not applicable, heterogeneity not calculable in this subgroup; NR, not reported. Changes in metabolic outcomes after use of oral contraceptives containing different progestins, by study duration. NA, not applicable, heterogeneity not calculable in this subgroup; NR, not reported. Most progestins induced a significant increase in plasma TG. The observed effect was largest for chlormadinone (pMD: 35.1 mg/dL; 95% CI: 3.4 to 66.8), followed by drospirenone (pMD: 33.3 mg/dL; 95% CI: 25.4 to 41.1), norgestimate (pMD: 28.5 mg/dL; 95% CI: 25.5 to 31.5), desogestrel (pMD: 27.4 mg/dL; 95% CI: 21.0 to 33.7), cyproterone (pMD: 25.6 mg/dL; 95% CI: 16.4 to 34.9), gestodene (pMD: 25.4 mg/dL; 95% CI: 21.1 to 29.7) and levonorgestrel (pMD: 12.1 mg/dL; 95% CI: 8.42 to 15.7) ( Figs 2 , 3 , 4 , 5 and 6 ). Only for norgestimate there was a difference between PCOS status subgroups, the impact on plasma TG was larger for studies in women without PCOS ( P  = 0.02 for interaction, Table 3 ). Table 3 Changes in metabolic outcomes after use of oral contraceptives containing different progestins, in participants with or without polycystic ovary syndrome. Outcome Subgroup N studies (participants) pMD (95% CI) I 2 P -value for difference between subgroups P -value for heterogeneity Cyproterone BMI PCOS 14 (306) −0.06 (−0.37, 0.24) 0 0.92 0.63 No PCOS 2 (44) −0.11 (−1.01, 0.78) 0 0.50 Glucose PCOS 13 (283) −2.26 (−3.97, −0.56) 51 <0.0001 0.02 No PCOS 1 (24) −6.11 (−3.97, −0.56) NA NA TG PCOS 17 (393) 25.1 (13.8, 36.4) 92 0.70 <0.0001 No PCOS 7 (167) 28.6 (15.1, 42.0) 88 <0.0001 HDL PCOS 16 (323) 6.09 (1.91, 10.3) 84 0.49 <0.0001 No PCOS 7 (157) 8.17 (3.95, 12.4) 85 <0.0001 LDL PCOS 17 (393) 0.08 (−8.01, 8.16) 83 0.80 <0.0001 No PCOS 6 (133) 1.49 (−6.23, 9.22) 72 0.003 Chlormadinone BMI PCOS 1 (20) 0.50 (−2.10, 3.10) NA 0.87 NA No PCOS 1 (12) 0.20 (−2.45, 2.85) NA NA Glucose PCOS 1 (20) −4.20 (−10.01, 1.61) NA 0.28 NA No PCOS 1 (12) 0 (−4.04, 5.04) NA NA TG PCOS 1 (20) 56.7 (17.6, 95.8) NA 0.12 NA No PCOS 1 (12) 23.0 (5.80, 40.2) NA NA HDL PCOS 1 (20) 8.90 (3.22, 14.6) NA 0.60 NA No PCOS 1 (12) 12.3 (1.01, 23.6) NA NA LDL PCOS 1 (20) 1.70 (−13.3, 16.7) NA 0.53 NA No PCOS 1 (12) −7.70 (−32.9, 17.5) NA NA Desogestrel BMI PCOS 2 (77) 0.48 (−0.82, 1.78) 41 0.64 0.19 No PCOS 6 (134) 0.12 (−0.57, 0.82) 0 0.78 Glucose PCOS 2 (77) 3.84 (−2.58, 9.54) 76 0.45 0.04 No PCOS 7 (204) 0.99 (−1.30, 3.29) 55 0.04 TG PCOS 2 (77) 15.7 (6.92, 24.6) 0 0.02 0.69 No PCOS 21 (460) 28.9 (22.3, 35.4) 70 <0.0001 HDL PCOS 2 (77) 3.99 (−0.43, 8.41) 59 0.17 0.12 No PCOS 24 (506) 7.26 (5.68, 8.83) 14 0.27 LDL PCOS 2 (77) 4.13 (−2.80, 11.1) 0 0.99 0.47 No PCOS 25 (505) 4.09 (−1.47, 9.65) 71 <0.0001 Drospirenone BMI PCOS 8 (202) −0.04 (−0.68, 0.61) 0 0.02 0.99 No PCOS 9 (274) −0.60 (−1.04, −0.16) 0 0.58 Glucose PCOS 6 (172) 0.12 (−2.63, 2.88) 80 0.33 0.0001 No PCOS 3 (322) 3.55 (−2.76, 9.85) 95 <0.0001 TG PCOS 7 (152) 32.0 (17.5, 44.6) 76 0.64 0.0003 No PCOS 8 (500) 35.1 (24.9, 45.2) 91 <0.0001 HDL PCOS 8 (202) 9.26 (4.84, 13.7) 75 0.30 0.0002 No PCOS 9 (529) 6.46 (3.65, 9.28) 78 <0.0001 LDL PCOS 8 (202) 3.44 (−4.29, 11.2) 68 0.99 0.003 No PCOS 9 (529) 1.30 (−4.70, 7.30) 87 <0.0001 Norgestimate BMI PCOS 2 (24) 6.14 (−1.49, 1.77) 0 0.95 0.69 No PCOS 1 (17) 0.20 (−0.75, 1.15) NA NA Glucose PCOS 2 (24) −0.16 (−2.45, 2.13) 0 0.30 0.50 No PCOS 1 (17) 1.80 (−1.09, 4.69) NA NA TG PCOS 3 (49) 27.4 (24.1, 30.8) 0 0.06 0.93 No PCOS 3 (74) 37.1 (27.5, 46.7) 74 0.02 HDL PCOS 2 (24) 0.21 (−2.45, 2.87) 0 0.02 0.45 No PCOS 2 (57) 8.70 (2.14, 15.3) 76 0.04 LDL PCOS 3 (49) 13.0 (4.37, 21.7) 77 0.47 0.01 No PCOS 2 (57) 9.54 (5.55, 13.5) 0 0.50 NA, not applicable, heterogeneity not calculable in this subgroup; NR, not reported. Changes in metabolic outcomes after use of oral contraceptives containing different progestins, in participants with or without polycystic ovary syndrome. NA, not applicable, heterogeneity not calculable in this subgroup; NR, not reported. Drospirenone caused a small reduction in BMI (pMD: –0.60 kg/m 2 ; 95% CI: –1.04 to –0.16). However, this effect was driven by a study among women without PCOS (( 65 ), pMD: –1.1 kg/m 2 ; 95% CI: –1.7 to –0.5; P  = 0.02 for interaction; Table 3 ). None of the other progestins included in this study had a significant impact on BMI ( Figs 2 , 3 , 5 , 6 and 7 ). None of the studied progestins had a significant impact on HOMA-IR. Women taking cyproterone showed a trivial yet statistically significant decrease in fasting plasma glucose (FPG) (pMD: –2.7 mg/dL; 95% CI: –4.8 to –0.7). This reduction was significantly larger in the only cyproterone study in participants without PCOS than in the studies among women with PCOS ( P  = 0.02 for interaction; Table 3 ). None of the other progestins showed a significant effect on FPG. Out of the 82 studies included, 32 were found to be of low ROB, 40 of medium ROB and 10 of high ROB ( Table 1 ). We performed a sensitivity analysis in which we removed the 10 studies with high ROB and repeated meta-analyses for all OCs and all metabolic outcomes (Supplementary Table 2). Despite minor numerical differences, the significance of modifications in metabolic parameters and the central results of the study remained the same. Visual examination of funnel plots and formal testing for publication bias with Egger’s and Begg’s tests revealed no indication of publication bias for most outcomes in most progestins (Supplementary Figs 1, 2, 3, 4 and 5). Four intervention-outcome pairs showed indication of publication bias: LDLc change after desogestrel, TG change after drospirenone, HDLc change after drospirenone and LDLc change after levonorgestrel. There was a study in which there was a 63 mg/dL increase in LDLc after use of a desogestrel-containing OC ( 51 ), this outlier contributed only 2.6% of the weighted mean difference but was largely responsible for an asymmetric funnel plot and significant Egger and Begg’s tests (Supplementary Fig. 2). Change in TG after drospirenone also exhibited an asymmetric funnel plot and significant Egger and Begg’s tests (Supplementary Fig. 3), but asymmetry was mainly due to small studies reporting larger increases in TG. After trim-and-fill analysis for these outcomes (Supplementary Fig. 6), only the modification of HDLc after drospirenone use was affected by publication bias adjustment, the increase in HDLc became smaller and borderline significant.

OCs containing different progestins have small, but potentially clinically important effects on the metabolic profile in premenopausal women. Most progestins increase plasma TG and some raise HDLc. In general, OCs have minor or no effects on LDLc, BMI, HOMA-IR and FPG. Baseline lipid and glucose testing should be considered to help determine the most appropriate OC prescription for women.

In this systematic review and meta-analysis, we estimated the effect of OCs containing different progestins on plasma lipids and other variables related to metabolic health, using data from randomized trials, including premenopausal women. The lipid fractions most influenced by OCs were plasma triglycerides and HDLc. All progestins except dienogest (whose studies did not report changes in TG) induced a significant increase in plasma TG, which ranged numerically between 12.1 mg/dL (levonorgestrel) and 35.1 mg/dL (chlormadinone), consistent with the existing literature from nonrandomized studies. Most of the newer progestins including chlormadinone, cyproterone, desogestrel and drospirenone induced statistically and clinically significant increases in HDLc, as had been found in previous studies in multiple different populations ( 88 ). Even though in observational studies gestodene induced significant increases in HDLc ( 2 ), our study showed a numerically marginal increase. Meanwhile, norgestimate did not affect HDLc and levonorgestrel significantly reduced it. Clinical trials of dienogest did not report on HDLc but a previous observational study of patients with endometriosis did show a tendency to lower it ( 89 ). On the other hand, the effect of OCs on plasma LDLc was generally more modest, and affected to the greater extent by the duration of use. The above-mentioned observational study of dienogest in endometriosis found no effect of dienogest on lipid profile variables ( 89 ), in contrast with our meta-analysis, which showed a 7 mg/dL decrease in LDLc. In accordance with earlier literature ( 3 ), levonorgestrel and norgestimate relevantly increased LDLc (7 and 11 mg/dL, respectively) ( Table 4 ). For progestins with an effect on LDLc, this effect was evident mostly for studies of long-term (>12 months) use. A recent randomized cross-over trial that compared OCs containing newer progestins vs levonorgestrel in women with PCOS found the largest positive impact for drospirenone, both in terms of anti-androgenic activity (reduction in free androgen index and acne) and modification of plasma lipids (reduction of LDLc and increase of HDLc) ( 90 ). Table 4 Summary of changes in metabolic outcomes after use of oral contraceptives containing different progestins in randomized clinical trials. Progestin in OC Metabolic outcome LDLc HDLc TG BMI FPG HOMA-IR Chlormadinone ↔ ↑ ↑ ↔ ↔ NA Cyproterone ↔ ↑ ↑ ↔ ↓ ↔ Desogestrel ↔ ↑ ↑ ↔ ↔ ↔ Dienogest ↓ NA NA NA NA NA Drospirenone ↔ ↑ ↑ ↓ ↔ ↔ Gestodene ↔ ↔↑ ↑ ↔ NA NA Levonorgestrel ↑ ↓ ↑ ↔ ↔ ↔ Norgestimate ↑ ↔ ↑ ↔ ↔ NA FPG, fasting plasma glucose; HDLc, HDL cholesterol; HOMA-IR, homeostasis model assessment-insulin resistance; LDLc, LDL cholesterol; NA, not available; TG, triglycerides. Summary of changes in metabolic outcomes after use of oral contraceptives containing different progestins in randomized clinical trials. FPG, fasting plasma glucose; HDLc, HDL cholesterol; HOMA-IR, homeostasis model assessment-insulin resistance; LDLc, LDL cholesterol; NA, not available; TG, triglycerides. Perhaps unexpectedly, we found a negligible or non-existent effect of OCs on body weight. Drospirenone use was accompanied by a significant yet small 0.6 kg/m 2 reduction in BMI, an effect that was not significant in prior individual observational studies or short-term trials ( 91 ). None of the other progestins affected BMI. Though few clinical trials were available, our analyses revealed that cyproterone use was associated with a slight decrease in plasma glucose. HOMA-IR, an index of insulin resistance in the fasting state, was not affected by any of the progestins included in our analyses. Interestingly, BMI did not appear to be a significant modifier of the metabolic effects for most of the studied OCs, and age was a significant modifier for only one of the outcomes (HDLc change after cyproterone). Thus, the intrinsic pharmacology of each OC seemed to be a greater determinant of its metabolic effect than its interaction with the patient’s age or BMI. A recent meta-analysis compared the effects of OCs on metabolic parameters, specifically in women with PCOS patients based on the type of progestin and duration of follow-up ( 88 ). Similar to our results, the most salient modifications in plasma lipids were increases in both triglycerides and HDLc, with elevations of HDLc occurring sooner than those of TG for most agents. This study also found a significant increase in LDL with use for 12 months or longer for all progestins, something that we also found for levonorgestrel, desogestrel, drospirenone and cyproterone; but not for dienogest, which in fact reduced LDLc. Also, in line with our results, this prior systematic review in PCOS found no impact of OCs on body weight or plasma glucose. We observed that the selection criteria for inclusion in this review resulted in a sample of studies with a reasonably low risk of bias. Most (72/82, or 87.8%) of the studies included were of low or medium risk of bias, and the exclusion of the remaining 10 studies did not modify the magnitude or significance of the modifications in metabolic parameters estimated in the complete sample. The main strengths of our study are the inclusion of clinical trials only, the analysis of OCs containing multiple different progestins and the study of various relevant metabolic outcomes. The fact that we restricted our search to studies of premenopausal women receiving OCs at contraceptive doses (as opposed to the doses used for hormonal replacement or for the treatment of endometriosis), may also have contributed to a reduced clinical heterogeneity of the studies. The meta-analysis addresses a relevant question and its results provide useful guidance for clinicians. The main limitations of our study include the presence of a fair amount of heterogeneity for most outcomes, and the scarcity of high-quality clinical trials reporting on variables related to carbohydrate metabolism like glycemia and HOMA-IR. In order to take into account the very likely existence of between-studies heterogeneity on the observed effects, we synthesized study results using random-effects models for all outcomes. Concerning the effects of OC’s on glycemia and HOMA-IR, it is important for these parameters to be included in future studies of OCs, in order to perform a more complete assessment of the physiological impact of hormonal contraception.

R J de Souza has served as an external resource person to the World Health Organization’s Nutrition Guidelines Advisory Group on tra fats, saturated fats, and polyunsaturated fats. The WHO paid for his travel and accommodation to attend meetings from 2012 to 2017 to present and discuss this work. He has also done contract research for the Canadian Institutes of Health Research’s Institute of Nutrition, Metabolism, and Diabetes, Health Canada, and the World Health Organization for which he received remuneration. He has received speaker’s fees from the University of Toronto, and McMaster Children’s Hospital. He has held grants from the Canadian Foundation for Dietetic Research, Population Health Research Institute, and Hamilton Health Sciences Corporation as a principal investigator, and is a co-investigator on several funded team grants from Canadian Institutes of Health Research. He serves as an independent director of the Helderleigh Foundation (Canada).

Four of every five reproductive-age women in the world have used oral contraceptives (OC) ( 1 ). Most OC combine one estrogen with one progestin so there are multiple possible combinations and dosing schemes. Although OC are highly effective for preventing pregnancy, their impact on lipid, lipoprotein, and carbohydrate metabolism is not fully acknowledged. First- and second-generation progestins (desogestrel, gestodene, norgestimate, levonorgestrel, and others) are chemically related to testosterone and may have been undesirable androgenic effects ( 2 ). Newer progestins derived from progesterone or spironolactone (cyproterone, chlormadinone, nomegestrol, drospirenone) are expected to result in a more favorable metabolic profile ( 2 ). Estrogens and progestins bind rapidly to nuclear receptors that ultimately regulate the transcription of target genes ( 2 ). Estrogens promote insulin secretion, peripheral glucose utilization, synthesis of triglycerides, secretion of HDL, and favor LDL cholesterol uptake and catabolism ( 3 ). On the other hand, progesterone induces insulin resistance and hyperglycemia, resembling the physiological state of pregnancy ( 4 ). Of note, progestins may bind not only the progesterone receptor, but also the glucocorticoid, mineralocorticoid and androgen receptors with different affinities ( 3 ). Androgen receptor binding may induce weight gain and higher plasma LDL cholesterol ( 2 ). Combined OC containing newer progestins like drospirenone and dienogest are considered anti-androgenic ( 3 ). Given that available studies have used combined OC with distinct combinations and doses of estrogen and progestin, using a wide variety of comparators, the overall impact of each OC on metabolic variables is not easy to assess. For these reasons, we conducted a pre–post effect size meta-analysis of randomized clinical trials in order to estimate a consolidated effect of OC containing different progestins on plasma lipid profile, body weight, glycemic levels, and insulin resistance, in adult premenopausal women.