Table 3 Risk factors of suspected developmental delays among Nepalese children (N = 2870).

From: Socioeconomic and education-based inequality in suspected developmental delays among Nepalese children: a subnational level assessment

Variables

Categories

Odds ratio (95% confidence interval)

Model 1a

Model 2b

Model 3c

Model 4d

Model 5e

Child characteristics

 Age of children

36–47 months (ref.)

1.00

1.00

1.00

1.00

1.00

48–59 months

0.51 (0.41–0.64)***

0.22 (0.15–0.32)***

0.20 (0.14–0.30)***

0.19 (0.13–0.29)***

0.19 (0.13–0.29)***

 Sex of children

Boys (ref.)

1.00

1.00

1.00

1.00

1.00

Girls

0.96 (0.80–1.17)

0.88 (0.63–1.23)

0.90 (0.64–1.26)

0.90 (0.64–1.27)

0.88 (0.62–1.24)

 Birth order

1 (ref.)

1.00

1.00

1.00

1.00

1.00

2–4

1.88 (1.41–2.51)***

2.60 (1.70–3.96)***

1.76 (1.14–2.73)**

1.56 (0.99–2.46)

1.41 (0.89–2.22)

 ≥ 5

2.24 (1.44–3.50)***

3.83 (1.89–7.76)***

1.98 (0.87–4.49)

1.55 (0.67–3.58)

1.20 (0.52–2.79)

 Stunting

No (ref.)

1.00

1.00

1.00

1.00

1.00

Yes

1.69 (1.38–2.08)***

2.43 (1.69–3.51)***

2.08 (1.44–2.99)***

1.93 (1.33–2.81)**

1.78 (1.22–2.58)**

Parent’s characteristics

 Mother’s age

15–24 years (ref.)

1.00

 

1.00

1.00

1.00

25–34 years

1.11 (0.88–1.40)

 

1.14 (0.75–1.73)

1.35 (0.87–2.08)

1.54 (0.99–2.38)

35 years and above

1.22 (0.87–1.69)

 

0.60 (0.32–1.13)

0.78 (0.41–1.49)

1.07 (0.56–2.06)

 Mother’s education

No education (ref.)

1.00

 

1.00

1.00

1.00

Basic education

0.58 (0.45–0.75)***

 

0.44 (0.28–0.70)***

0.51 (0.32–0.83)**

0.67 (0.41–1.08)

Secondary education

0.34 (0.27–0.44)***

 

0.16 (0.09–0.27)***

0.22 (0.13–0.38)***

0.30 (0.17–0.52)***

Higher education

0.18 (0.10–0.30)***

 

0.05 (0.02–0.12)***

0.09 (0.03–0.26)***

0.12 (0.05–0.34)***

Household-level characteristics

 Household socio-economic status

Poorest (ref.)

1.00

  

1.00

1.00

Poorer

0.75 (0.55–1.04)

  

0.56 (0.32–0.97)*

0.47 (0.26–0.85)*

Middle class

0.56 (0.42–0.75)***

  

0.44 (0.25–0.77)**

0.33 (0.18–0.62)**

Richer

0.53 (0.37–0.76)***

  

0.53 (0.29–0.96)*

0.41 (0.21–0.79)**

Richest

0.24 (0.16–0.37)***

  

0.15 (0.07–0.33)***

0.13 (0.05–0.31)***

 Household size

1–4 persons (ref.)

1.00

  

1.00

1.00

5–6 persons

0.93 (0.74–1.15)

  

0.89 (0.59–1.34)

0.87 (0.58–1.32)

 > 6 persons

1.11 (0.82–1.49)

  

1.07 (0.65–1.79)

1.08 (0.64–1.80)

 Iodine level in the salt consumed

None (0 ppm) (ref.)

1.00

  

1.00

1.00

Inadequate (< 15 ppm)

1.18 (0.72–1.94)

  

0.93 (0.37–2.33)

0.96 (0.38–2.42)

Adequate (≥ 15 ppm)

1.11 (0.70–1.74)

  

0.86 (0.37–1.99)

1.00 (0.43–2.32)

Community-level characteristics

 Place of residence

Urban area (ref.)

1.00

   

1.00

Rural area

1.41 (1.12–1.75)**

   

1.27 (0.83–1.94)

 Province

Province 1 (ref.)

1.00

   

1.00

Madhesh province

2.64 (1.75–3.98)***

   

6.37 (3.03–13.37)***

Bagmati Province

1.18 (0.78–1.78)

   

2.24 (1.07–4.67)*

Gandaki Province

0.86 (0.54–1.37)

   

1.01 (0.43–2.39)

Lumbini Province

2.22 (1.44–3.42)***

   

4.01 (1.96–8.21)***

Karnali Province

2.72 (1.72–4.30)***

   

2.34 (0.99–5.53)

Sudhurpashchim Province

2.23 (1.45–3.37)***

   

2.57 (1.19–5.56)***

Random-effects parameters

 Community level

Variance

 

1.66

1.12

1.03

0.75

ICC

 

0.15

0.10

0.10

0.07

 Household level

Variance

 

6.23

6.39

6.43

6.50

ICC

 

0.70

0.70

0.69

0.69

Model comparison

 Likelihood ratio testf

Chi-square statistic

 

314.86

289.15

277.51

257.21

P value

 

 < 0.001

 < 0.001

 < 0.001

 < 0.001

 AIC

  

3097

3026

2854

2831

 BIC

  

3144

3103

2977

2996

  1. ref.  reference category, ppm parts per million, SD standard deviation, SE standard error.
  2. ***p < 0.001, **p < 0.01, *p < 0.05.
  3. aModel 1: crude models.
  4. bModel 2: only child characteristics were included in the model.
  5. cModel 3: additionally adjusted for parental characteristics.
  6. dModel 4: additionally adjusted for household related characteristics.
  7. eModel 5: additionally adjusted for community characteristics.
  8. fBased on the results on likelihood ratio tests, estimates of multilevel logistic regression models were preferred than fixed effect models.
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