| Author | Year Country | Study design | Outcome | Number (Case) | Dietary Investigation tool | UPF consumption | OR (95%CI or P value) | Covariate |
|---|
| MARTIN[23] | 2015 USA | Cohort | Preterm birth | 3 143 (364) | FFQ | Western dietary pattern maximum vs minimum | OR=1.53 (1.02, 2.30) | Maternal age, race, pre-pregnancy BMI, educational level, marital status, parity, family income, smoking status in the first 6 months of pregnancy and energy intake | | ENGLUND-ÖGGE[24] | 2014 Norway | Cohort | Preterm birth | 66 000 (3 505) | FFQ | Western dietary pattern | HR=1.12 (1.01, 1.25) P>0.05 | Maternal history of previous preterm delivery, maternal age, height, pre-pregnancy BMI, marital status, parity, smoking, education level, family income, and total energy intake | | ENGLUND-ÖGGE[25] | 2012 Norway | Cohort | Preterm birth | 60 761 (3 281) | MoBa FFQ | Sugar -sweetened beverages maximum vs minimum Artificially sweetened maximum vs minimum | OR=1.11 (1.00, 1.24) OR=1.25 (1.08, 1.45) | Maternal history of previous preterm delivery, maternal age, pre-pregnancy BMI, marital status, parity, smoking, education level and total energy intake | | RODRIGUES[26] | 2020 Brazil | Cross -sectional | LBW | 99 (13) | Form of food consumption markers in the food and nutrition surveillance system | maximum vs minimum | OR=1.46 (1.02, 2.10) | Maternal age, marital status, education level, per capita income, prenatal weight, final fetal weight, increase in gestational age and gestational age, type of delivery, number of pregnancies | | FERREIRA[27] | 2022 Brazil | Cross -sectional | LBW | 260 (8) | FFQ | Dietary pattern 3 (rich in ultra-processed foods) | OR=1.27 (1.11, 1.45) | Maternal age, pre-pregnancy BMI, education level, marital status, family income and parity | | VIEIRA E SOUZA[28] | 2022 Brazil | Cross -sectional | LBW | 626 (43) | FFQ | maximum vs minimum | OR=1.72 (1.09, 2.70) | Maternal age, pre-pregnancy BMI, education level, percapita income, marital status, gestational weight gain, parity, number of prenatal consultations, smoking and physical activity level | | SCHRUBBE[29] | 2024 Brazil | Cohort | LGA | 214 (22) | 24hDietary Rcall | maximum vs minimum | OR=1.03 (1.00, 1.06) | Maternal age, pre-pregnancy BMI, race, education level, family income, marital status, parity, smoking and alcohol consumption | | ROCHA[30] | 2022 Brazil | Cross -sectional | SGA | 300 (17) | FFQ | UPF energy proportion>2.06% vs <0.31% | OR=10.4 (1.33, 8090) | Maternal age, pre-pregnancy BMI, total energy intake, education level, family income, marital status, parity, smoking, alcohol consumption and race | | VICTOR[31] | 2023 Brazil | Cross -sectional | SGA LBW | 2 632 314 (186 206/188 450) | / | maximum vs minimum | OR=1.04 (1.02, 1.06) OR=1.13 (1.11, 1.16) | Maternal age, marital status, education level, gestational age, number of prenatal appointments, newborn gender and race | | LEONE[32] | 2021 Spain | Cohort | GDM | 3 730 (186) | FFQ | <3 servings/d vs >4.5servings/d | OR=1.10 P=0.82 | Maternal age, pre-pregnancy BMI, education level, smoking, physical activity, family history of diabetes, parity, time spent watching TV, hypertension, nutritional therapy and total energy intake | | LAMYIAN[33] | 2017 Iran | Cohort | GDM | 1 026 (71) | FFQ | maximum vs minimum | OR=2.12 (1.12, 5.43) | Maternal age, pre-pregnancy BMI, physical activity, family history of diabetes, history of GDM, smoking, drug use and total energy intake | | YISAHAK[34] | 2022 USA | Cohort | GDM PE | 1 948 (85/63) | FFQ | maximum vs minimum | OR=0.68 (0.44, 1.05) OR=0.99 P=0.85 OR=1.33 P=0.63 | Maternal age, pre-pregnancy BMI, race, family income, education level, marital status, parity, physical activity, sleep duration and total energy intake | | SEDAGHAT[14] | 2017 Iran | Case -control | GDM | 388 (122) | FFQ | Western dietary pattern | OR=1.68 (1.04, 2.27) | Maternal age, pre-pregnancy BMI, gestational age, education level, socioeconomic status, smoking, family history of diabetes and supplement use | | ASADI[35] | 2019 Iran | Case -control | GDM | 278 (130) | FFQ | Western dietary pattern | OR=1.50 (0.74, 3.03) P=0.2 | Maternal age, physical activity level, family history of diabetes, pre-pregnancy BMI, education level, occupational status, history of fetal macrosomia and total energy intake | | DONAZAR-EZCURRA[36] | 2018 Spain | Cohort | GDM | 3 396 (172) | FFQ | Soft drink intake > 400 g/w | OR=2.03 (1.25, 3.31) | Maternal age, pre-pregnancy BMI, family history of diabetes, smoking, total energy intake, physical activity, parity, fast food intake, adherence to Mediterranean dietary patterns, alcohol intake, multiple pregnancies and cardiovascular disease/hypertension | | BRANTSAETER[15] | 2009 Norway | Cohort | PE | 23 423 (1 267) | FFQ | Western dietary pattern | OR=1.21 (1.03, 1.42) | Maternal age, pre-pregnancy BMI, education level, smoking, pre-pregnancy hypertension status, dietary supplement use and total energy intake | | IKEM[37] | 2019 Danmark | Cohort | Gestationalhypertension PE | 55 139 (5 491) | FFQ | Western dietary pattern | Gestational hypertension OR=1.18 (1.05, 1.33) PE OR=1.40 (1.11, 1.76) | Maternal age, pre-pregnancy BMI, parity, smoking, physical activity level, paired sociodemographic status, total energy intake and previous history of hypertension |
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