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. 2018 Sep 19;9:1238. doi: 10.3389/fphys.2018.01238

Table 2.

Characteristics of enrolled studies on risk assessment of blood adiponectin level on metabolic syndrome incidence.

Data source (Author, country, year) Population Study Adiponectin MetS Risk assessment
Base-line Features Age (year) Gender (F/M) Follow up (year) Category Sample Measurement Definition Incidence (N, %) Indicator Comparison (μg/ml) Extent Methods Adjusted covariates
Seino et al., Japan, 2009 1. General population
2. Without MetS, endocrine disease, renal or hepatic disease
3. Without medication for diabetes
MetS:
46.6 ± 9.2
0/416 6 Total Serum ELISA Japanese criteria 27, 6.4 OR T1 vs. T3 (≥7.44 vs. ≤ 4.65) 0.45
0.17–1.19)
Chi-square NA
Non-MetS:
44.1 ± 8.3
HMW HR ≤ 2.65 vs. >2.65 1.56
(1.05–2.29)
Cox hazard model Age and BMI
OR T1 vs.T3 (≥5.07 vs. ≤ 3.16) 0.24
(0.08–0.75)
Chi-square NA
Nakashima et al., Japan, 2011 1. General population 2. without MetS and DM Non-MetS (M):
61.2 ± 16.0
312/224 3.2 Total Plasma ELISA AHA/NHLBI M: 46,20.5 HR M: SD (5.7) incre-ment vs. before 0.68
(0.51–0.92)
Cox hazards model NA
Non-Mets (F):
59.8 ± 13.2
F: 43, 13.8 HR F: SD (6.6) incre-ment vs. before 0.63
(0.46–0.87)
Cox hazards model NA
Men MetS (M):
60.8 ± 14.8
HMW HR M: SD (4.3) incre-ment vs. before 0.69
(0.51–0.93)
Cox hazards model Age, BMI, OGTT, and HOMA-IR
MetS (F):
63.3 ± 10.4
HR F: SD (5.5) incre-ment vs. before 0.70
(0.51–0.96)
Cox hazards model Ditto
Juonala et al., Finland, 2011 1. General population
2. without MetS
Non-MetS:
31.5 ± 5.0
659/829 6 Total Serum RIA NCEP-ATPIII M: 102, 12.3 OR 1 unit increment vs. before 0.94
(0.90–0.99)
Logistic regression Age, sex, BMI, LDL-C, CRP,
MetS:
33.0 ± 4.7
F: 133, 20.2 leptin, insulin, smoking, family history of CVD, WC, HDL-C, TG, SBP and FBG
Kim et al., Korea, 2013b 1. General Population
2. without any MetS components
3. without CAD history
MetS (M):
56.0 ± 8.1
1,231/831 2.6 Total Serum RIA Modified NCEP-ATP-III M: 153, 18.4 OR M: Q4 vs. Q1 (>11.22/ < 5.94) 0.25
(0.14-0.47)
Logistic regression Age, BMI, LDL-C, smoking, exercise, CRP, HOMA-IR and TG.
Non-MetS (M):
56.6 ± 8.2
F: 199, 16.2 OR M: 5 unit incre-ment vs. before 0.82
(0.73–0.92)
Logistic regression DITTO
MetS (F):
55.4 ± 7.8
OR F: Q4 vs. Q1 (>15.24/ < 8.91) 0.45
(0.28–0.74)
Logistic regression DITTO
Non-MetS (F): 52.5 ± 7.9 OR F: 5 unit incre-ment vs. before 0.90
(0.83–0.96)
Logistic regression DITTO
Hata et al., Japan, 2015 1. General population
2. Without MetS
40.4 ± 0.5 0/365 3.1 Total Serum RIA IDF 45, 12.3 OR Q4 vs Q1 (≥8.9 vs. ≤ 4.9) 0.14
(0.04–0.48)
Chi-square NA
Lindberg et al., Denmark, 2017 1. General population
2.Without MetS, CVD, DM
3. Without medication on MetS
Q1:42 ± 8 406/747 9.4 Total Plasma Immuno-fluoro-metric assay NCEP-ATP-III criteria 187,16.2 OR Q1 vs. Q4 (≤ 6.6 vs. >12.5) 2.24
(1.11–4.52)
Logistic-regression Age, gender, smoking, physical activity, SBP, DBP, FBG, BMI, TC, HDL, LDL, and eGFR.
Q2:44 ± 8 OR Per 1 unit decre-ment vs. before 1.56
(1.10–2.23)
Logistic-regression DITTO
Q3:45 ± 9
Q4:49 ± 8

BMI, body mass index; CRP, C-reactive protein; CVD,cardiovascular disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; ELISA, enzyme-linked immunoabsorbent assay; F, female; FBG, fasting blood glucose; HDL-C, high density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; HR, hazard ratio; LDL-C, low density lipoprotein cholesterol; M, male; MetS, metabolic syndrome; NA, not available; OGTT, oral glucose tolerance test; OR, odds ratio; Q, quantile; RIA, radioimmuno assay; SBP, systolic blood pressure; SD, standard deviation; TC, total cholesterol; TG, triglyceride; WC, waist circumference.