Table 7 Factors associated with SCB in CKD patients

Age (n = 7)

Ahn et al., [20]

Age ≥ 65 years was not significantly correlated with SCB (β = 0.14, p = 0.059).

Wang, et al., [19]

The self-care score was 4.83 points (p < 0.001) higher for patients older than 65 years than for younger patients.

Almutary & Tayyib, [22]

Age was negatively correlated with SCB (β = −0.183; p = 0.004).

Washington et al., [27]

Patients older than 70 were significantly associated with the self-management behavior of fluid adherence (p = 0.04).

Avanji et al., [30]

Age was not significantly correlated with SCB (β = − 0.11, p = 0.005)

He et al., [31]

Age was significantly associated with the disease cognition domain (F = 3.664; p = 0.028).

Age was not significantly associated with the domain of treatment management (F = 1.797, p = 0.170), exercise behaviors (F = 0.989, p = 0.375), diet behaviors (F = 1.000, p = 0.371), emotional management (F = 1.099, p = 0.336), and self-management knowledge (F = 1.868, p = 0.159).

Yu et al., [4]

● Age was positively correlated with exercise domain (β = 0.05, p = 0.03).

● Age was negatively correlated with the home blood pressure monitoring domain (β = -0.04, p = 0.02).

Age was not significantly correlated with the domain of diet (β = -0.01, p = 0.59), smoking habits (β = 0.03, p = 0.07), medication adherence (β = 0.03, p = 0.34) and total SCB (β = 0.05, p = 0.4).

Education level (n = 7)

Wang, et al., [19]

The self-care score was 3.238 points (p = 0.033) higher for college and above than for no degree.

Almutary & Tayyib, [22]

High school or less was not significantly correlated with SCB (β = 0.023; p = 0.705).

Lai et al., [23]

Having an education level of senior high school or above increased the odds ratio for having high self-management to 4.47 (p-values < 0.05).

Suarilah & Lin [8]

The level of education showed a significant association with self-management (t = 3.25, p = 0.023).

Kim & Cho, [29]

College or above (t = 1.80, p = 0.076) and high school (t = 1.69, p = 0.095) was not significantly associated with SCB

He et al., [31]

Education was significantly associated with the emotional management domain (F = 7.165; p = 0.004).

Education was not significantly associated with the domain of treatment management (F = 1.236, p = 0.309), exercise behaviors (F = 2.025, p = 0.155), diet behaviors (F = 1.016, p = 0.378), disease cognition (F = 1.236, p = 0.309) and self-management knowledge (F = 0.207, p = 0.815).

Yu et al., [4]

Senior high school or above was correlated with the domain of diet (β = 1.82, p = 0.001), home blood pressure monitoring (β = 1.70, p < 0.001), and medication adherence (β = -1.42, p = 0.04).

Senior high school or above was not correlated with the domain of exercise (β = 0.99, p = 0.08), smoking habits (β = -0.43, p = 0.27) and total SCB (β = 2.65, p = 0.08).

Health literacy (HL) (n = 4)

Yu et al., [4]

● HL was positively correlated with the domain of diet (βadj = 0.15, p < 0.005), exercise (βadj = 0.11, p = 0.004) and total SCB (βadj = 0.27; p = 0.008).

● The patients with sufficient or excellent health literacy had higher diet (β = 1.80, p = 0.003), exercise (βadj = 1.22, p = 0.02), and home blood pressure monitoring (βadj = 1.03, p = 0.03) performance than those with inadequate or limited/problematic health literacy.

Chen et al., [21]

HL was positively correlated with SCB (r = 0.33; p < 0.001).

Suarilah & Lin [8]

● HL showed a positively significant correlation with total self-management (r = 0.536), self-integration (r = 0.457), problem-solving (r = 0.528), and seeking social support (r = 0.381).

● HL (r = − 0.200) negatively correlated with adherence to the recommended regimen.

Ahn et al., [20]

HL (Actively managing my health) was correlated with SCB (β = 0.41; p < 0.001).

Comorbidity (n = 4)

Suarilah & Lin [8]

Family history of comorbidity (F = 6.28, p = 0.013) showed a significant association with SM.

Avanji et al., [30]

Being diabetic was associated with SCB (β=-0.09; p = 0.01).

Yu et al., [4]

Patients with diabetes mellitus were correlated with the home blood pressure monitoring domain (β = -0.80, p = 0.08).

● Patient with hypertension was not significantly correlated with the domain of diet (β = -0.43, p = 0.41), exercise (β = -0.51, p = 0.34), home blood pressure monitoring (β = 0.07, p = 0.88), smoking habits (β = 0.24, p = 0.52), medication adherence (β = -0.49, p = 0.47) and total SCB (β = -1.13, p = 0.44).

● Patient with diabetes mellitus was not significantly correlated with the domain of diet (β = 0.27, p = 0.62), exercise (β = -0.63, p = 0.25), smoking habits (β = 0.25, p = 0.53), medication adherence (β = 0.13, p = 0.85) and total SCB (β = -0.79, p = 0.60).

● Patient with heart disease was not significantly correlated with the domain of diet (β = 0.50, p = 0.46), exercise (β = -0.69, p = 0.31), home blood pressure monitoring (β = -0.20, p = 0.73), smoking habits (β = -0.31, p = 0.52), medication adherence (β = 0.23, p = 0.79) and total SCB (β = -0.47, p = 0.80).

Wang et al., [19]

The number of comorbidities was not a significant difference in self-care score among 2–3 comorbidities (p = 0.412), and 4 + comorbidities than 0–1 comorbidities (p = 0.705).

Social support (n = 4)

Kim & Cho, [29]

Social support increased SCB (β = 0.56, p < 0.001).

Chen et al., [21]

● Social support was correlated with SCB (r = 0.64; p < 0.001)

● Social support from healthcare providers (r = 0.60) and family (r = 0.50) was strongly correlated with SCB

Noviana & Zahra, [28]

There was a significant relationship between high social support and self-management (p = 0.027, odds ratio = 2.386).

Chen et al., [32]

After the 6-month intervention, the self-management ability of the intervention group was significantly different from that of the control group (P < 0.01).

Occupation (n = 3)

He et al., [31]

The occupation was associated with the domain of treatment management (F = 1.770; p = 0.032), exercise behaviors (F = 12.019; p = 0.001), diet behaviors (F = 6.032; p = 0.015), and disease cognition (F = 7.370; p = 0.008).

Employed status was not significantly associated with the domain of emotional management (F = 0.201, p = 0.655) and self-management knowledge (F = 1.897, p = 0.171).

Ahn et al., [20]

Not working was correlated with SCB (β = 0.16, p = 0.037).

Yu et al., [4]

The worker was correlated with the domain of exercise (β = -1.24, p = 0.02), smoking habits (β = -0.98, p = 0.008) and total SCB (β = -2.60, p = 0.07).

The worker was not significantly correlated with the domain of diet (β = -0.07, p = 0.89), home blood pressure monitoring (β = 0.44, p = 0.33), and medication adherence (β = -0.75, p = 0.28).

Body mass index (BMI) (n = 3)

Wang, et al., [19]

The self-care score was 2.24 points lower for patients with a BMI ≥ 24 kg/m² than BMI ≤ 24 kg/m² (p = 0.005).

Almutary & Tayyib, [22]

BMI was negatively associated with SCB (β = −0.159; p = 0.010).

Yu et al., [4]

BMI was correlated with the domain of diet (β = -0.15, p = 0.02), home blood pressure monitoring (β = -0.12, p = 0.04) and total SCB (β = −0.38, p = 0.04).

BMI was not significantly correlated with the domain of exercise (β = -0.12, p = 0.07), smoking habits (β = -0.02, p = 0.71), and medication adherence (β = 0.03, p = 0.74).

Marital status (n = 3)

Wang, et al., [19]

The self-care score was 1.826 points (p = 0.0411) higher for married or partnership than for single.

Yu et al., [4]

Married was not significantly correlated with the domain of diet (β = -0.42, p = 0.51), exercise (β = 0.36, p = 0.58), home blood pressure monitoring (β = -0.40, p = 0.46), smoking habits (β = -0.05, p = 0.92), medication adherence (β = -0.72, p = 0.39) and SCB (β = -1.22, p = 0.49).

Wembenyui et al., [24]

Levels of CKD self-management were significantly higher in patients who were married than those who were not (p < 0.01).

Laboratory result (n = 3)

Yu et al., [4]

Log-transformed triglycerides (β = −7.91, p = 0.01) and log-transformed urine PCR (β = −2.45, p = 0.04) were significantly negatively correlated with SCB.

The laboratory result was not significantly correlated with SCB:

• eGFR (ml/min/1.73m2) (β = 0.01, p = 0.71)

• Hemoglobin (g/dl) (β = 0.13, p = 0.72)

• Albumin (g/dl) (β = 1.74, p = 0.29)

• Uric acid (mg/dl) (β = 0.93, p = 0.02)

• Cholesterol (mg/dl) (β = -0.00, p = 0.93)

• Log-formed glycated hemoglobin (β =-1.17, p = 0.06)

Chen et al., [32]

● There were significant differences between the WeChat group and the face-to-face group for hemoglobin and blood phosphorus (p < 0.05).

● There were significant differences in albumin, hemoglobin, blood phosphorus, and calcium levels between the intervention and control groups after 3 months and 6 months of intervention (p < 0.01).

Ahn et al., [20]

The laboratory result was not significantly correlated with SCB:

• Serum hemoglobin ≥ 11 g/dl (within range) (β = -0.06, p = 0.426)

• Serum calcium < 8.5 or > 10.2 mg/dl (β = -0.03, p = 0.69)

• Serum creatinine > 1.3 mg/dl (β = 0.06, p = 0.717)

• Serum eGFRd ≥ 60 ml/min/1.73m² (within range) (β = 0.16, p = 0.382).

Duration of CKD diagnosis (n = 3)

Yu et al., [4]

CKD duration was positively correlated with total SCB (β = 0.51, p = 0.004) and exercise domain (β = 0.26, p < 0.001)

CKD duration was not significantly correlated with the domain of diet (β = 0.05, p = 0.49), home blood pressure monitoring (β = 0.03, p = 0.54), smoking habits (β = 0.07, p = 0.12), and medication adherence (β = 0.10, p = 0.25).

Almutary & Tayyib, [22]

Time aware of CKD 0–12 months (less than a year) was associated with SCB (β = −0.050; p = 0.405).

Wang et al., [19]

Duration of CKD diagnosis was not significantly different in self-care score among 3–4 years (0.424 points, p = 0.742) and 5 + years (1.327 points, p = 0.234) than < 3 years.

Gender (n = 2)

Yu et al., [4]

The female was correlated with the domain of exercise (β = -1.36, p = 0.01), medication adherence (β = -1.35, p = 0.04) and total SCB (β = −3.27, p = 0.02).

The female was not significantly correlated with the domain of diet (β = -0.60, p = 0.25), home blood pressure monitoring (β = -0.27, p = 0.54), and smoking habits (β = -0.32, p = 0.39).

Wang et al., [19]

Self-care score was 2.00 points (p = 0.020) higher for females than for males.

Disease Knowledge (n = 2)

Almutary & Tayyib, [22]

DK was negatively correlated with SCB (β = − 0.513; p < 0.0001).

Wembenyui et al., [24]

CKD knowledge was not significantly correlated with CKD self-management behavior (r = 0.02, p = 0.90).

Income (n = 2)

Suarilah & Lin [8]

Monthly income (F = 6.14, p = 0.014) was a significant association with the total score for self-management.

He et al., [31]

Income was not significantly associated with the domain of treatment management (F = 1.975, p = 0.143), exercise behaviors (F = 0.461, p = 0.632), diet behaviors (F = 1.99, p = 1.141), emotional management (F = 0.127, p = 0.881), disease cognition (F = 2.130, p = 0.446), and self-management knowledge (F = 0.812, p = 0.446).

Smoking status (n = 2)

Yu et al., [4]

Smokers were negatively correlated with SCB (β = −9.10, p = 0.001).

Smoker was not significantly correlated with the domain of diet (β = -1.69, p = 0.08), exercise (β = -1.20, p = 0.23), home blood pressure monitoring (β = -1.05, p = 0.20), and medication adherence (β = -0.89, p = 0.48).

Ahn et al., [20]

Not smoking was correlated with SCB (β = 0.32; p = 0.002).

Health education session (n = 2)

Wang, et al., [19]

Participating in the CKD integrated care program had significantly higher self-care scores than no participation (p < 0.001).

Yu et al., [4]

The number of health education sessions was correlated with the domain of exercise (β = 0.10, p < 0.001), smoking habits (β = 0.03, p = 0.04) and total SCB (β = 0.21, p = 0.001).

The number of health education sessions was not significantly correlated with the domain of diet (β = 0.02, p = 0.39), home blood pressure monitoring (β = 0.01, p = 0.75), and medication adherence (β = 0.06, p = 0.05).

Stage of CKD (n = 2)

Wang, et al., [19]

CKD stage 2 or higher had significantly higher self-care scores (p < 0.001).

Ahn et al., [20]

ESRD was correlated with SCB (β = 0.3; p = 0.004).

Psychology (n = 2)

Cardol et al., [25]

● CSI total was significantly correlated with psychological distress (β_adj = 1.04, p = 0.001), depressive symptoms (β_adj = 1.09, p = < 0.001), and anxiety symptoms (β_adj = 1.06, p = 0.018).

• Psychological distress was negatively associated with domain dietary adherence (β_adj = − 0.13, p = 0.006), physical activity (β_adj = − 0.13, p = 0.01), and medication adherence (β_adj = − 0.15, p = 0.002).

● Depressive symptoms were negatively associated with domain dietary adherence (β_adj = − 0.14, p = 0.004), physical activity (β_adj = − 0.15, p = 0.002), and medication adherence (β_adj = − 0.15, p = 0.002).

● Anxiety symptoms were negatively associated with domain dietary adherence (β_adj = − 0.11, p = 0.03) and medication adherence (β_adj = − 0.13, p = 0.009).

• Psychological distress was not significantly associated with domain body mass index (β_adj = 0.09, p = 0.07) and smoking (β_adj = 1.04, p = 0.13).

• Depressive symptoms were not significantly associated with domain body mass index (β_adj = 0.08, p = 0.09) and smoking (β_adj = 1.07, p = 0.07).

• Anxiety symptoms were not significantly associated with domain body mass index (β_adj = 0.05, p = 0.35), smoking (β_adj = 1.04, p = 0.38), and physical activity (β_adj = − 0.07, p = 0.19).

Lai et al., [23]

Depression was associated with SM (0.246; p = 0.03).

Treatment adherence

(n = 1)

Kim & Cho, [29]

Treatment adherence (t = 5.94, p < 0.001) was significantly associated with SCB.

Self-efficacy

(n = 1)

Wembenyui et al., [24]

A positive relationship was found between CKD self-management and self-efficacy (r = 0.37, p < 0.01), with high levels of self-efficacy associated with high levels of CKD self-management.

Resilience (n = 1)

Avanji et al., [30]

Resilience was associated with SCB (β = 0.78, p = 0.001).

Illness Perception (n = 1)

Kajiwara & Morimoto, [26]

Illness perception was associated with SCB (F = 7.31, p < 0.001).

Duration of dialysis (n = 1)

Kim & Cho, [29]

Duration of dialysis was not significantly associated with SCB (t = − 0.66, p = 0.514)

Living status (n = 1)

Ahn et al., [20]

Living status with family or someone was not significantly associated with SCB (β = 0.04, p = 0.644).