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  • Research article
  • Open Access
  • Open Peer Review

Growth patterns from birth to 24 months in Chinese children: a birth cohorts study across China

BMC Pediatrics201818:344

https://doi.org/10.1186/s12887-018-1328-z

  • Received: 1 May 2018
  • Accepted: 25 October 2018
  • Published:
Open Peer Review reports

Abstract

Background

Assessment of child growth is important in detecting under- and over-growth. We aimed to examine the growth patterns of healthy Chinese infants from birth to 24 months.

Methods

This study was based on six recent birth cohorts across China, which provided data (from 2015) on 4251 children (2174 boys, 2077 girls) who were born at term to mothers without gestational or preexisting diabetes, chronic hypertension, preeclampsia, or eclampsia. Analyses were performed using 28,298 longitudinal anthropometric measures in 4251 children and the LMS method to generate smoothed Z-score growth curves, which were compared to the WHO growth standards (which are based on data from 2003) and current Chinese growth references (which are based on data from 2005).

Results

Most (80.3%) of mother had college education or more, and maternal smoking was rare (0.4%). Compared to the WHO longitudinal growth standards for children aged 0 to 2 years, the growth references from this longitudinal study (length-, weight-, head circumference-, BMI-for-age, and weight-for-length) were significantly higher, for boys and girls; Specifically, the median length-, weight-, head circumference-, BMI-for-age, and weight-for-length was on average 0.9 (range 0.2–1.3) cm, 0.51 (range 0.09–0.74) kg, 0.17 (range − 0.24 to 0.37) cm, 0.70 (range 0.01 to 0.92) kg/m2, and 0.43 (range 0.01 to 1.07) kg higher in Chinese boys, and 1.3 (range 0.5–1.9) cm, 0.73 (range 0.10–0.91) kg, 0.45 (range 0.15–0.62) cm, 0.7 (range 0.0 to 1.0) kg/m2, and 0.42 (range 0.00 to 0.64) kg greater in Chinese girls, respectively. Compared to the current China cross-sectional growth references (based on data from a decade ago), growth references from this study were also higher, but the difference was less than that between growth references of this study and WHO growth standards.

Conclusions

This recent multicenter prospective birth cohort study examined early growth patterns in China. The new growth curves represent the growth patterns of healthy Chinese infants evaluated longitudinally from 0 to 24 months of age, and provide references for monitoring growth in early life in modern China that are more recent than WHO longitudinal growth standards from other countries and previous cross-sectional growth references for China.

Keywords

  • Growth standards
  • Chinese children
  • Infancy

Background

The assessment of child growth is important in detecting under- and over-growth, which can provide information for timely intervention. The first 1000 days of life (from conception to 2 years of age) is a period of rapid growth and development, and vulnerable to nutritional and environmental influences [1]. Identifying normal child growth patterns is of fundamental importance in growth assessment.

Both the World Health Organization (WHO) growth standards [2] and the China growth references [3] are being applied in China. The WHO growth standards for children aged 0 to 24 months were constructed based on longitudinal data of children (n = 882) by using selection criteria of having socioeconomic conditions favorable to growth and having access to breastfeeding support (for qualifying as “standard”) from the WHO Multicenter Growth Reference Study (MGRS) conducted in six countries from 1997 to 2003 (without a site in China). The China growth charts were constructed from a large (n = 44,250) cross-sectional study based on stratified random sampling of children in nine cities of China, which was conducted from May to October in 2005 [3]. Comparison of the growth curves over the restricted range of ages from 0 to 2 years indicated the reference for China was significant higher for BMI for boys and girls. However, the comparisons were complicated by differences in inclusion/exclusion criteria (for the WHO sample, strict criteria about known constraints on growth and cooperation with feeding recommendations, which led to over 80% of mother-infant pairs being ineligible; for the China sample, multistage stratified cluster sampling was used based on urban/suburban areas, districts, and community, with several exclusion criteria), as well as by differences in the design of the studies (longitudinal for the WHO study and cross-sectional for the study in China). The difference between China growth references and WHO growth standards could have been an artifact, so confirmation study is warranted.

Historically, in some circumstances, secular trends of height have occurred from one generation to the next generation [4]. China has a diverse population, environment, dietary habits and tradition, and it is going through rapid modernization and urbanization. Early child growth has drawn much attention since these factors may affect growth. China started the 1st National Survey on the Physical Growth and Development of Children (NSPGDC) in the nine cities of China in 1975, and conducted the survey every 10 years from 1975 to 2005 to address possible secular trends, with the most recent data (from 2005) providing the current references for growth in China [3] (but in need of a 10-year update in 2015). Longitudinal data from a sample with stricter inclusion/exclusion criteria would provide a better comparison to the WHO standards. A small cohort [5] recruited in 2007 (n = 1531 retained up to 1 year of age) with strict WHO criteria applied showed significant differences (heavier in weight, longer in length, and bigger in head circumference) compared to WHO standards, as well as compared to the current cross-sectional references, which showed similar differences (except for the 97th percentiles that were lower rather than higher).

Long-term follow-up data has enormous value in evaluating the optimal individual growth trajectory, which may not be captured by cross-sectional data [3, 6]. Between 2012 and 2014, six longitudinal birth cohort studies were launched in China. A number of common exposures shared by all cohorts were collected and common outcomes were observed, which formed the foundation of China Birth Cohort Consortium (CBCC). This collaboration provided, for the first time in China, longitudinal growth data from birth cohorts from various regions of the country, but it still is a convenience sample from an efficient combination of cohorts.

This report examines growth patterns from birth to 24 months in Chinese children by pooling the individual level anthropometric follow-up measures from CBCC. The growth references from the 2015 CBCC will be used for comparison to the 2006 WHO longitudinal growth standards and the 2005 China cross-sectional growth references to provide an update on how healthy infants are growing in modern China.

Methods

Study population and data collection

This study used data from six birth cohorts of CBCC which were located at Shanghai (2 cohorts), Anhui, Guangdong, Hubei, and Jiangsu Provinces and were initiated between 2012 and 2014 (Additional file 1: Table S1_1 and S1_2). Additional file 1: Table S1_2 presents the study objective of each of the 6 cohorts. The original aims of these prospective cohorts were to study the environmental, genetic and behavioral factors during pregnancy and in early childhood, and their effects on pregnancy outcomes, fetal and child growth and development, and risks of diseases. Pregnant women were recruited at hospitals when they came for their routine prenatal care visits.

Weight, length, head circumference, and gestational age at birth were obtained from obstetrical medical records. Child anthropometric measurements including weight, length, and head circumference were conducted by trained study staff or trained pediatric nurses in maternal and child health care centers according to the WHO protocol at 7 targeted ages (42 days, 3, 6, 9, 12, 18 and 24 months; http://www.who.int/childgrowth/training/en/). Recumbent length on infants was measured with infant head position in the Frankfort Vertical Plane, and the soles of the feet flat on the moveable footboard. The cohort staffs were trained by group-watching WHO training video course on weight, length, and head circumference. The pediatric nurse measurements were made as routine care was provided. Infant age was calculated by date at measurement minus date of birth. Feeding type in the first 6 months was classified into three types: exclusive breastfeeding, mixed feeding (i.e., combination of breastfeeding and formula feeding), and exclusive/only formula feeding [7]. Infant passive smoking exposure was defined by the mother or father smoking, or for anyone else living in the home smoking. The diagnosis of gestational diabetes mellitus (GDM) in pregnant women was based on the recommendations of International Association of Diabetes and Pregnancy Study Groups (IADPSG) [8].

For this project, we requested each of the six birth cohort studies to contribute longitudinal child growth data of 1000 singleton children from birth to 2 years of age, or maximum number available at the time of our data request in July, 2016. Two cohorts contributed child follow-up measurements up to 12 months due to later starting date (2014) or child follow-up schedule (Additional file 1: Table S1). The inclusion criteria included singleton live births. The exclusion criteria included: (1) infants born with congenital malformations; (2) pregnancy conceived by assisted reproductive technologies (ART); (3) women with medical complication of sexually transmitted diseases (syphilis, HIV infection, and AIDS); (4) women with pre-existed diabetes. There were 5152 mother-child pairs, which provided a sample almost 6 times greater than the WHO longitudinal cohort from 2003 and over 3 times greater than the previous China longitudinal cohort from 2007. While birth cohort studies used better trained personnel for the growth assessments, more observations can also offset “imprecise observations”.

Among the 5152 mothers, 672 had GDM, 213 had preterm deliveries (gestational age < 37 weeks), and 71 had hypertensive disorders in pregnancy. Among the remaining 4258, 7 had missing data on infant sex. To generate the growth references, we used data from 4251 normal term-born children and excluded children of mothers with GDM, hypertensive disorders in pregnancy (e.g., chronic hypertension, gestational hypertension, preeclampsia and eclampsia),children born preterm to avoid the potential influences of known prenatal risk factors [1012],and children with missing data on sex.

Statistical analysis

We used the LMS method to fit smooth z-score curves for length, weight, head circumference and BMI according to age, and for weight according to length respectively in normal term-born healthy children, stratified by infant sex. [13] The three curves of median (M), coefficient of variation (S) and skewness (L, which is expressed as a Box-Cox power) across age/or length were fitted as cubic splines by using maximum penalized likelihood [13]. The z-score of child growth measures y (length, weight, head circumference and BMI) at time t (or length t, for weight-for-length) was calculated from the smooth curve L(t), M(t), and S(t) by the formula:
$$ z=\frac{{\left[y/M(t)\right]}^{L(t)}-1}{L(t)S(t)},\mathrm{if}\kern0.5em L\left(\mathrm{t}\right)\ne 0;\kern0.5em z=\frac{\log \left[y/M\left(\mathrm{t}\right)\right]}{S\left(\mathrm{t}\right)},\mathrm{if}\kern0.5em L\left(\mathrm{t}\right)=0 $$

By using the maximum penalized likelihood and LMS method, all available data of infants from birth to 27 months, including those followed up to 12 months were able to be used to estimate the smoothing parameters and generate the smoothed curves [9, 13]. The age-based references were truncated at 24 completed months to avoid the right-edge effect [14]. We compared z-scores of 0, ±2, and ± 3 for the growth measures in this study with the WHO standards (http://www.who.int/childgrowth/standards/en/), and the China 2005 references for children aged 0 to 2 years [3], both of which were constructed using similar LMS methods for smoothing procedures [3, 14]. The two-sided t-test was used to test statistical significance of the difference at a p < 0.05. The growth curves were constructed by using LMSchartmaker Pro version 2.54 software (Medical Research Council, UK).

We also calculated the 3rd, 10th, 50th, 90th and 97th percentiles of all growth measures in both boys and girls by age with subgroup sample size > 100 observations to summarize our data (without using smoothing technique), and compared these percentiles with WHO standards to show the differences. The analyses were conducted by using SAS 9.4 software (SAS Institute, Cary, North Carolina).

Results

This report presented the z-score curves of 4251 children who were born at term to mothers without gestational or preexisting diabetes, chronic hypertension, preeclampsia, or eclampsia. A total of 28,298 anthropometric measures were obtained from ages 0 to 27 months (Additional file 1: Tables S2 and S3). All were urban children. 51.1% were boys and 54.0% were delivered via C-section. The mean maternal and paternal height was 161.4 (SD 4.9) cm and 174.4 (SD 5.3) cm, respectively. Mean (pre-pregnancy) BMI was 20.6 (SD 2.8) kg/m2 for mothers and 23.9 (SD 3.3) kg/m2 for fathers. As expected, boy infants had greater birthweight, length and head circumference than girl infants (Table 1). Most (80.3%) of mother had college education or more and 98.3% of mother were Han ethnicity. During the first 6 months, most (77.6%) of infants were mixed fed, and 13.4% had exclusive breast-feeding. In the first 2 years, 27.9% of children were exposed to passive-smoking. There was no sex difference for these factors (Table 1). Over the follow-up assessments (see Fig. 1), the children aged 0 to 2 years in this cohort were taller, heavier, and had greater head circumference than the children in the WHO cohort.
Table 1

Characteristics of 4251 mothers, fathers and children by child sex

 

Infant sex

p value

 

Boy

Girl

Sample size

2174

2077

 

Maternal factors

 Maternal age (years)

28.7 ± 3.4

28.6 ± 3.5

0.51

 Pre-pregnancy weight (kg)

53.8 ± 7.8

53.7 ± 8.1

0.92

 Maternal height (cm)

161.3 ± 4.9

161.4 ± 5.0

0.33

 Prepregnancy BMI (kg/m2)

20.7 ± 2.8

20.6 ± 2.8

0.46

Mother Education

 Junior high school or lower

136(6.3)

135(6.6)

0.90

 High school

287(13.4)

266(13.0)

 

 College or above

1725(80.3)

1641(80.4)

 

Mother smoke during pregnancy

 Yes

10(0.5)

7(0.3)

0.53

 No

2148(99.5)

2047(99.7)

 

Parity

 Primiparous

1958(90.2)

1885(90.9)

0.44

 parous

212(9.8)

188(9.1)

 

Mode of Delivery

 Vaginal delivery

994(45.8)

957(46.2)

0.79

 C-section

1177(54.2)

1115(53.8)

 

Paternal factors

 Father age (years)

30.6 ± 4.4

30.6 ± 4.6

0.69

 Father height (cm)

174.2 ± 5.2

174.6 ± 5.3

0.04

 Father weight (kg)

72.5 ± 11.2

73.1 ± 11.7

0.14

 Father BMI (kg/m2)

23.9 ± 3.2

23.9 ± 3.3

0.56

Father smoke during mother pregnancy

 Yes

568(32.1)

567(34.0)

0.25

 No

1199(67.9)

1101(66.0)

 

Infant factors

 Birth weight (g)

3399 ± 404

3309 ± 392

< 0.001

 Birth length (cm)

50.2 ± 1.4

49.8 ± 1.3

< 0.001

 Birth head circumference (cm)

34.1 ± 1.1

34.0 ± 1.0

0.01

 Gestational age (weeks)

39.1 ± 1.0

39.3 ± 1.0

< 0.001

Breastfeeding Type (0–6 months)

 Formula feeding

168(8.7)

172(9.4)

0.36

 Exclusive Breastfeeding

252(13.0)

252(13.7)

 

 Mixed feeding

1518(78.3)

1412(76.9)

 

Children passive smoking

 No

1187(72.7)

1125(71.5)

0.44

 Yes

445(27.3)

448(28.5)

 

Data were presented as mean ± SD, and n (%)

χ2 test for categorical variables and t-test for continuous variables

Fig. 1
Fig. 1

Comparison of growth-for-age z-score curves with WHO standards in boys and girls

Length-for-age

Table 2 presents the growth references of length-for-age at 0, ±1, ±2, and ± 3 SD in our study. In comparison with the corresponding WHO growth standard from 0 to 24 months of age, the median length-for-age was on average 0.9 cm (range 0.2–1.3 cm) higher in Chinese boys, and 1.3 cm (range 0.5–1.9 cm) higher in Chinese girls (Fig. 1). Similarly, for z-score of − 2 (i.e. the cutoffs for defining stunting), child length was on average 1.1 cm taller (range 0.8–1.8 cm) in Chinese boys and 1.6 (range 1.1–2.0) cm taller in Chinese girls than the corresponding sex-specific WHO curves. Likewise, for z-score of − 3 was higher in Chinese boys and girls across age.
Table 2

Length (cm)-for-age z-score curves at 0, ±1, ±2, and ± 3 SD for Chinese boys and girls from birth to 24 months

Age (month)

Boys

Girls

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

0

−0.7996

50.3

0.0306

46.0

47.4

48.8

50.3

51.9

53.6

55.3

−1.0973

49.9

0.0305

45.7

47.0

48.4

49.9

51.5

53.2

55.0

1

−0.7996

54.9

0.0318

50.1

51.6

53.2

54.9

56.7

58.6

60.6

−0.9519

54.2

0.0320

49.4

50.9

52.5

54.2

55.9

57.9

59.9

2

−0.7996

58.9

0.0326

53.6

55.3

57.1

58.9

60.9

63.0

65.3

−0.6922

57.9

0.0331

52.6

54.3

56.0

57.9

59.9

62.0

64.2

3

−0.7996

62.2

0.0330

56.6

58.3

60.2

62.2

64.3

66.6

69.0

−0.3981

61.0

0.0338

55.3

57.1

59.0

61.0

63.2

65.4

67.7

4

− 0.7996

64.8

0.0331

58.9

60.8

62.8

64.8

67.1

69.4

71.9

−0.1356

63.6

0.0342

57.4

59.4

61.4

63.6

65.8

68.1

70.5

5

−0.7996

67.0

0.0332

60.9

62.8

64.8

67.0

69.3

71.7

74.3

0.0640

65.7

0.0343

59.2

61.3

63.5

65.7

68.0

70.3

72.8

6

−0.7996

68.8

0.0331

62.6

64.5

66.6

68.8

71.2

73.7

76.3

0.2052

67.5

0.0344

60.8

63.0

65.2

67.5

69.9

72.3

74.8

7

−0.7996

70.5

0.0330

64.0

66.1

68.2

70.5

72.9

75.4

78.1

0.2974

69.1

0.0344

62.2

64.5

66.8

69.1

71.5

74.0

76.5

8

−0.7996

71.9

0.0330

65.4

67.4

69.6

71.9

74.4

76.9

79.7

0.3533

70.6

0.0344

63.5

65.8

68.2

70.6

73.0

75.6

78.1

9

−0.7996

73.2

0.0329

66.6

68.7

70.9

73.2

75.7

78.3

81.1

0.3867

71.9

0.0344

64.7

67.1

69.5

71.9

74.4

77.0

79.6

10

−0.7996

74.4

0.0329

67.7

69.8

72.0

74.4

76.9

79.6

82.5

0.4064

73.1

0.0343

65.8

68.2

70.7

73.1

75.7

78.3

80.9

11

−0.7996

75.5

0.0328

68.7

70.8

73.1

75.5

78.1

80.8

83.7

0.4167

74.3

0.0342

66.9

69.3

71.8

74.3

76.9

79.5

82.1

12

−0.7996

76.6

0.0328

69.7

71.9

74.2

76.6

79.2

82.0

84.9

0.4203

75.4

0.0342

67.9

70.3

72.8

75.4

78.0

80.6

83.3

13

−0.7996

77.7

0.0328

70.7

72.9

75.2

77.7

80.3

83.1

86.1

0.4205

76.5

0.0341

68.9

71.4

73.9

76.5

79.1

81.8

84.5

14

− 0.7996

78.8

0.0328

71.7

73.9

76.3

78.8

81.5

84.3

87.3

0.4189

77.6

0.0341

69.9

72.4

74.9

77.6

80.2

82.9

85.7

15

−0.7996

79.9

0.0327

72.7

74.9

77.3

79.9

82.6

85.4

88.5

0.4166

78.6

0.0340

70.9

73.4

76.0

78.6

81.3

84.1

86.9

16

−0.7996

81.0

0.0327

73.7

76.0

78.4

81.0

83.7

86.6

89.7

0.4142

79.7

0.0339

71.8

74.4

77.0

79.7

82.5

85.2

88.1

17

−0.7996

82.1

0.0327

74.7

77.0

79.4

82.1

84.8

87.8

90.9

0.4125

80.8

0.0339

72.8

75.4

78.1

80.8

83.6

86.4

89.2

18

−0.7996

83.1

0.0327

75.6

78.0

80.5

83.1

85.9

88.9

92.1

0.4121

81.8

0.0338

73.8

76.4

79.1

81.8

84.6

87.5

90.4

19

−0.7996

84.1

0.0327

76.6

78.9

81.5

84.1

87.0

90.0

93.2

0.4134

82.9

0.0337

74.7

77.4

80.1

82.9

85.7

88.6

91.5

20

−0.7996

85.2

0.0327

77.5

79.9

82.4

85.2

88.0

91.1

94.3

0.4154

83.9

0.0336

75.7

78.3

81.1

83.9

86.7

89.6

92.6

21

−0.7996

86.1

0.0327

78.4

80.8

83.4

86.1

89.0

92.1

95.4

0.4169

84.9

0.0336

76.6

79.3

82.0

84.9

87.7

90.7

93.7

22

−0.7996

87.1

0.0327

79.3

81.7

84.3

87.1

90.0

93.2

96.5

0.4172

85.8

0.0335

77.5

80.2

83.0

85.8

88.8

91.7

94.7

23

−0.7996

88.1

0.0327

80.1

82.6

85.3

88.1

91.0

94.2

97.5

0.4164

86.8

0.0335

78.4

81.1

83.9

86.8

89.8

92.7

95.8

24

−0.7996

89.0

0.0327

81.0

83.5

86.2

89.0

92.0

95.2

98.6

0.4146

87.8

0.0334

79.2

82.0

84.9

87.8

90.7

93.8

96.8

Compared to the China growth reference (2005 data), the median length-for-age in our study (2015 data) was on average 0.3 cm higher in boys, and 0.5 cm higher in girls across age (Fig. 2). This might be evidence of a small secular trend. The comparisons to the 2005 China references were more similar than that for the comparisons to the WHO standards (Figs. 1 and 2).
Fig. 2
Fig. 2

Comparison of growth-for-age z-score curves from China 2015 data (the present study) with those from China 2005 data in boys and girls

Weight-for-age

Table 3 presents the growth reference of weight-for-age at 0, ±1, ±2, and ± 3 SD in our study. For weight-for-age z-score of − 2 (cutoff point for defining underweight), weight was on average 0.60 (range 0.13–0.94) kg heavier in Chinese boys and 0.80 (range 0.19–1.10) kg heavier in Chinese girls than those of WHO standards across age (Fig. 1).
Table 3

Weight (kg)-for-age z-score curves at 0, ±1, ±2, and ± 3 SD for Chinese boys and girls from birth to 24 months

Age (months)

Boys

Girls

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

0

0.3325

3.39

0.1213

2.30

2.63

2.99

3.39

3.82

4.28

4.78

0.0359

3.30

0.1196

2.30

2.59

2.92

3.30

3.71

4.18

4.71

1

0.3465

4.70

0.1196

3.21

3.66

4.16

4.70

5.29

5.92

6.60

−0.0184

4.51

0.1182

3.17

3.56

4.01

4.51

5.08

5.71

6.44

2

0.3315

5.87

0.1178

4.03

4.59

5.20

5.87

6.59

7.36

8.20

−0.0550

5.48

0.1168

3.88

4.35

4.88

5.48

6.17

6.94

7.81

3

0.2872

6.87

0.1159

4.76

5.41

6.11

6.87

7.70

8.60

9.57

−0.0886

6.46

0.1155

4.60

5.14

5.76

6.46

7.26

8.16

9.19

4

0.2373

7.61

0.1143

5.32

6.01

6.78

7.61

8.52

9.51

10.58

−0.1129

7.13

0.1145

5.09

5.69

6.37

7.13

8.01

9.00

10.13

5

0.1874

8.16

0.1130

5.75

6.48

7.28

8.16

9.13

10.18

11.33

−0.1331

7.63

0.1137

5.47

6.10

6.82

7.63

8.56

9.62

10.82

6

0.1414

8.61

0.1118

6.11

6.86

7.69

8.61

9.62

10.73

11.95

−0.1515

8.06

0.1130

5.79

6.45

7.20

8.06

9.03

10.14

11.41

7

0.1005

9.00

0.1107

6.42

7.19

8.05

9.00

10.05

11.20

12.48

−0.1690

8.45

0.1122

6.09

6.78

7.56

8.45

9.46

10.62

11.95

8

0.0648

9.34

0.1098

6.69

7.48

8.36

9.34

10.42

11.61

12.93

−0.1858

8.81

0.1115

6.37

7.08

7.89

8.81

9.86

11.07

12.45

9

0.0344

9.62

0.1089

6.92

7.73

8.62

9.62

10.72

11.95

13.31

−0.2003

9.11

0.1109

6.60

7.33

8.16

9.11

10.19

11.43

12.85

10

0.0082

9.86

0.1082

7.12

7.94

8.85

9.86

10.99

12.24

13.64

−0.2125

9.34

0.1103

6.78

7.53

8.38

9.34

10.44

11.71

13.17

11

−0.0159

10.08

0.1076

7.30

8.13

9.05

10.08

11.22

12.50

13.93

−0.2238

9.54

0.1098

6.94

7.70

8.56

9.54

10.67

11.95

13.44

12

−0.0398

10.29

0.1069

7.48

8.32

9.25

10.29

11.45

12.75

14.21

−0.2356

9.74

0.1093

7.10

7.87

8.74

9.74

10.88

12.19

13.70

13

−0.0650

10.51

0.1062

7.67

8.51

9.45

10.51

11.69

13.01

14.50

−0.2487

9.94

0.1088

7.26

8.04

8.93

9.94

11.10

12.43

13.97

14

−0.0919

10.73

0.1055

7.86

8.71

9.66

10.73

11.93

13.28

14.79

−0.2635

10.15

0.1082

7.44

8.23

9.13

10.15

11.33

12.69

14.26

15

−0.1199

10.95

0.1048

8.05

8.91

9.87

10.95

12.17

13.54

15.09

−0.2798

10.37

0.1076

7.61

8.41

9.33

10.37

11.57

12.95

14.55

16

−0.1485

11.18

0.1040

8.24

9.11

10.08

11.18

12.41

13.81

15.39

−0.2974

10.59

0.1070

7.80

8.61

9.53

10.59

11.81

13.21

14.84

17

−0.1776

11.40

0.1033

8.43

9.30

10.29

11.40

12.65

14.07

15.68

−0.3161

10.81

0.1063

7.98

8.80

9.74

10.81

12.05

13.47

15.13

18

−0.2070

11.62

0.1026

8.62

9.50

10.49

11.62

12.88

14.32

15.96

−0.3357

11.03

0.1057

8.16

8.99

9.94

11.03

12.28

13.73

15.42

19

−0.2365

11.83

0.1019

8.80

9.69

10.70

11.83

13.11

14.58

16.25

−0.3558

11.24

0.1051

8.34

9.18

10.14

11.24

12.51

13.98

15.70

20

−0.2659

12.04

0.1012

8.99

9.88

10.89

12.04

13.34

14.82

16.52

−0.3766

11.45

0.1045

8.51

9.36

10.33

11.45

12.73

14.23

15.98

21

−0.2953

12.24

0.1006

9.17

10.07

11.09

12.24

13.56

15.06

16.79

−0.3981

11.65

0.1039

8.69

9.54

10.53

11.65

12.96

14.48

16.25

22

−0.3246

12.45

0.0999

9.35

10.26

11.28

12.45

13.78

15.30

17.06

−0.4204

11.86

0.1033

8.86

9.73

10.72

11.86

13.18

14.72

16.53

23

−0.3539

12.65

0.0993

9.53

10.44

11.47

12.65

13.99

15.54

17.33

−0.4432

12.07

0.1027

9.04

9.91

10.92

12.07

13.41

14.97

16.81

24

−0.3832

12.85

0.0986

9.71

10.62

11.66

12.85

14.21

15.77

17.59

−0.4665

12.28

0.1021

9.22

10.10

11.11

12.28

13.63

15.21

17.08

Compared to China reference from 2005 data, the weight-for-age median in our study (China 2015 data) was on average 0.25 kg higher (range 0.07–0.33 kg) in boys, and 0.34 kg higher (range 0.09–0.42 kg) in girls across age (Fig. 2).

Head circumference-for-age

Table 4 presents the growth reference of head circumference-for-age at 0, ±1, ±2, and ± 3 SD in our study. At the z-score of − 2, head circumference was 0.36 cm greater (range 0.08 to 0.86 cm) in Chinese boys, and 0.76 cm greater (range 0.54 to 1.04 cm) in Chinese girls, than the corresponding WHO standards (Fig. 1).
Table 4

Head circumference (cm)-for-age z-score curves at 0, ±1, ±2, and ± 3 SD for Chinese boys and girls from birth to 24 months

Age (months)

Boys

Girls

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

0

−7.0263

34.3

0.0262

32.2

32.8

33.4

34.3

35.3

36.6

38.4

−1.4337

34.1

0.0300

31.3

32.1

33.1

34.1

35.1

36.3

37.5

1

−4.4686

37.3

0.0280

34.8

35.5

36.4

37.3

38.5

39.8

41.5

−1.2431

36.9

0.0304

33.9

34.8

35.8

36.9

38.1

39.3

40.7

2

−2.7515

39.2

0.0291

36.3

37.1

38.1

39.2

40.4

41.8

43.3

−1.0791

38.6

0.0304

35.4

36.4

37.4

38.6

39.8

41.1

42.5

3

−1.7763

40.6

0.0294

37.4

38.4

39.5

40.6

41.8

43.2

44.7

−0.9472

40.0

0.0303

36.6

37.7

38.8

40.0

41.2

42.5

43.9

4

−1.2600

41.7

0.0295

38.3

39.4

40.5

41.7

43.0

44.3

45.8

−0.8444

41.0

0.0301

37.6

38.6

39.8

41.0

42.2

43.6

45.0

5

−0.9752

42.6

0.0293

39.2

40.2

41.4

42.6

43.9

45.3

46.7

−0.7629

41.8

0.0298

38.4

39.5

40.6

41.8

43.1

44.5

45.9

6

−0.7968

43.4

0.0291

39.9

41.0

42.1

43.4

44.7

46.0

47.5

−0.6960

42.6

0.0295

39.1

40.2

41.4

42.6

43.9

45.2

46.7

7

−0.6658

44.1

0.0289

40.5

41.6

42.8

44.1

45.4

46.7

48.2

−0.6377

43.3

0.0292

39.7

40.9

42.0

43.3

44.6

45.9

47.4

8

−0.5616

44.7

0.0286

41.1

42.2

43.4

44.7

46.0

47.4

48.8

−0.5863

43.9

0.0289

40.3

41.5

42.6

43.9

45.2

46.5

48.0

9

−0.4796

45.2

0.0284

41.6

42.7

43.9

45.2

46.5

47.9

49.3

−0.5444

44.3

0.0286

40.8

41.9

43.1

44.3

45.6

47.0

48.4

10

−0.4171

45.6

0.0282

41.9

43.1

44.3

45.6

46.9

48.2

49.7

−0.5097

44.7

0.0283

41.2

42.3

43.5

44.7

46.0

47.4

48.8

11

−0.3699

45.9

0.0280

42.3

43.4

44.7

45.9

47.2

48.6

50.0

−0.4793

45.1

0.0280

41.5

42.6

43.8

45.1

46.3

47.7

49.1

12

−0.3349

46.2

0.0278

42.6

43.8

45.0

46.2

47.5

48.9

50.3

−0.4516

45.4

0.0278

41.8

42.9

44.1

45.4

46.6

48.0

49.4

13

−0.3116

46.5

0.0277

42.9

44.1

45.3

46.5

47.8

49.2

50.6

−0.4262

45.6

0.0275

42.1

43.2

44.4

45.6

46.9

48.3

49.6

14

−0.3002

46.8

0.0275

43.2

44.3

45.6

46.8

48.1

49.5

50.9

−0.4029

45.9

0.0273

42.3

43.5

44.7

45.9

47.2

48.5

49.9

15

−0.2977

47.1

0.0274

43.4

44.6

45.8

47.1

48.4

49.7

51.1

− 0.3819

46.1

0.0271

42.6

43.7

44.9

46.1

47.4

48.7

50.1

16

−0.2997

47.3

0.0273

43.6

44.8

46.0

47.3

48.6

49.9

51.4

−0.3629

46.3

0.0269

42.8

43.9

45.1

46.3

47.6

48.9

50.3

17

−0.3039

47.4

0.0272

43.8

45.0

46.2

47.4

48.8

50.1

51.5

−0.3456

46.5

0.0267

43.0

44.1

45.3

46.5

47.8

49.1

50.5

18

−0.3091

47.6

0.0271

43.9

45.1

46.3

47.6

48.9

50.3

51.7

−0.3293

46.7

0.0265

43.2

44.3

45.5

46.7

48.0

49.3

50.6

19

−0.3155

47.8

0.0270

44.1

45.3

46.5

47.8

49.1

50.4

51.9

−0.3135

46.9

0.0263

43.4

44.5

45.7

46.9

48.1

49.4

50.8

20

− 0.3232

47.9

0.0269

44.3

45.5

46.7

47.9

49.3

50.6

52.0

−0.2976

47.1

0.0261

43.6

44.7

45.9

47.1

48.3

49.6

50.9

21

−0.3320

48.1

0.0268

44.5

45.6

46.9

48.1

49.4

50.8

52.2

−0.2811

47.2

0.0260

43.7

44.9

46.0

47.2

48.5

49.8

51.1

22

−0.3414

48.3

0.0267

44.6

45.8

47.0

48.3

49.6

51.0

52.4

−0.2641

47.4

0.0258

43.9

45.1

46.2

47.4

48.7

50.0

51.3

23

−0.3506

48.5

0.0266

44.8

46.0

47.2

48.5

49.8

51.1

52.6

−0.2473

47.6

0.0256

44.1

45.3

46.4

47.6

48.9

50.1

51.5

24

−0.3592

48.6

0.0265

45.0

46.1

47.4

48.6

49.9

51.3

52.7

−0.2313

47.8

0.0254

44.3

45.4

46.6

47.8

49.0

50.3

51.6

Compared to cross-sectional 2005 norms for China, the median head circumference-for-age in our study was similar in boys, but on average 0.3 cm greater (range 0.1–0.7 cm) in girls across age (Fig. 2).

BMI-for-age

Table 5 presents the growth reference of BMI-for-age at 0, ±1, ±2, and ± 3 SD in our study. As shown in Fig. 1, median BMI-for-age was on average 0.70 kg/m2 (range 0.01 to 0.92 kg/m2) higher in Chinese boys, and 0.7 (range 0.0 to 1.0) kg/m2 higher in Chinese girls than the corresponding WHO standards across the age of 0–24 months. For z-score of 2, BMI on average ~ 0.70 kg/m2 higher in Chinese boys and girls than the WHO standards.
Table 5

BMI-for-age z-score at 0, ±1, ±2, and ± 3 SD for Chinese boys and girls from birth to 24 months

Age (month)

Boys

Girls

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

0

0.1590

13.4

0.0958

10.0

11.0

12.2

13.4

14.7

16.2

17.8

−0.1727

13.3

0.0920

10.1

11.1

12.1

13.3

14.5

16.0

17.6

1

0.7178

15.6

0.0943

11.4

12.8

14.2

15.6

17.1

18.6

20.2

−0.0900

15.4

0.0898

11.8

12.9

14.1

15.4

16.8

18.4

20.2

2

0.6937

16.7

0.0930

12.3

13.7

15.2

16.7

18.3

19.9

21.6

−0.1078

16.2

0.0891

12.5

13.6

14.8

16.2

17.7

19.4

21.3

3

0.6483

17.7

0.0920

13.1

14.6

16.1

17.7

19.4

21.1

22.8

−0.1322

17.2

0.0886

13.3

14.5

15.8

17.2

18.8

20.6

22.6

4

0.6054

18.1

0.0909

13.5

14.9

16.5

18.1

19.8

21.5

23.3

−0.1567

17.7

0.0880

13.6

14.8

16.2

17.7

19.3

21.1

23.1

5

0.5683

18.2

0.0899

13.6

15.1

16.6

18.2

19.9

21.6

23.4

−0.1810

17.7

0.0875

13.7

14.9

16.3

17.7

19.4

21.2

23.2

6

0.5384

18.2

0.0890

13.6

15.1

16.6

18.2

19.8

21.6

23.4

−0.2055

17.7

0.0869

13.8

15.0

16.3

17.7

19.4

21.2

23.2

7

0.5161

18.2

0.0880

13.7

15.1

16.6

18.2

19.8

21.5

23.3

−0.2298

17.8

0.0863

13.8

15.0

16.3

17.8

19.4

21.2

23.2

8

0.5000

18.1

0.0871

13.7

15.1

16.6

18.1

19.7

21.4

23.2

−0.2535

17.7

0.0857

13.8

15.0

16.3

17.7

19.3

21.1

23.1

9

0.4888

18.0

0.0862

13.7

15.0

16.5

18.0

19.6

21.3

23.0

−0.2763

17.6

0.0851

13.8

14.9

16.2

17.6

19.2

21.0

23.0

10

0.4814

17.9

0.0854

13.6

14.9

16.4

17.9

19.4

21.0

22.7

−0.2981

17.5

0.0845

13.7

14.8

16.1

17.5

19.0

20.8

22.7

11

0.4767

17.7

0.0846

13.5

14.8

16.2

17.7

19.2

20.8

22.5

−0.3192

17.3

0.0839

13.6

14.7

15.9

17.3

18.8

20.6

22.5

12

0.4735

17.6

0.0838

13.4

14.7

16.1

17.6

19.1

20.6

22.3

−0.3398

17.2

0.0834

13.5

14.6

15.8

17.2

18.7

20.4

22.3

13

0.4713

17.4

0.0830

13.4

14.7

16.0

17.4

18.9

20.5

22.1

−0.3598

17.0

0.0828

13.4

14.5

15.7

17.0

18.5

20.2

22.1

14

0.4693

17.3

0.0823

13.3

14.6

15.9

17.3

18.8

20.3

21.9

−0.3794

16.9

0.0823

13.4

14.4

15.6

16.9

18.4

20.0

21.9

15

0.4673

17.2

0.0816

13.3

14.5

15.8

17.2

18.6

20.1

21.7

−0.3984

16.8

0.0818

13.3

14.3

15.5

16.8

18.2

19.9

21.7

16

0.4654

17.1

0.0809

13.2

14.4

15.7

17.1

18.5

19.9

21.5

−0.4169

16.7

0.0814

13.2

14.2

15.4

16.7

18.1

19.7

21.5

17

0.4635

16.9

0.0802

13.1

14.3

15.6

16.9

18.3

19.7

21.3

−0.4349

16.5

0.0809

13.1

14.1

15.3

16.5

18.0

19.6

21.4

18

0.4616

16.8

0.0795

13.0

14.2

15.5

16.8

18.2

19.6

21.1

−0.4524

16.4

0.0805

13.1

14.1

15.2

16.4

17.8

19.4

21.2

19

0.4598

16.7

0.0789

13.0

14.2

15.4

16.7

18.0

19.4

20.9

−0.4695

16.3

0.0801

13.0

14.0

15.1

16.3

17.7

19.3

21.1

20

0.4581

16.6

0.0783

12.9

14.1

15.3

16.6

17.9

19.3

20.7

−0.4862

16.2

0.0797

13.0

13.9

15.0

16.2

17.6

19.2

20.9

21

0.4564

16.5

0.0777

12.9

14.0

15.2

16.5

17.8

19.2

20.6

−0.5024

16.2

0.0793

12.9

13.9

15.0

16.2

17.5

19.1

20.8

22

0.4547

16.4

0.0772

12.8

14.0

15.2

16.4

17.7

19.0

20.4

−0.5181

16.1

0.0789

12.9

13.8

14.9

16.1

17.4

19.0

20.7

23

0.4531

16.3

0.0766

12.8

13.9

15.1

16.3

17.6

18.9

20.3

−0.5334

16.0

0.0786

12.8

13.8

14.8

16.0

17.4

18.9

20.6

24

0.4516

16.2

0.0761

12.8

13.9

15.0

16.2

17.5

18.8

20.2

−0.5482

16.0

0.0782

12.8

13.7

14.8

16.0

17.3

18.8

20.5

Compared to the China corresponding growth references from 2005 data, the median BMI-for-age in our study was on average 0.3 kg/m2 higher in boys and 0.4 kg/m2 higher in girls across age (Fig. 2).

Weight-for-length

Table 6 presents the growth references of weight-for-length at 0, ±1, ±2, and ± 3 SD in our study. Median weight-for-length was on average 0.43 kg greater (range 0.01 to 1.07 kg) than WHO standards in boys, and 0.42 kg greater (range 0.00 to 0.64 kg) in Chinese girls from body length > 50 cm (Fig. 3), but lighter weight at the very short length in Chinese girls (< 52 cm).
Table 6

Weight (kg)- for-length (cm) z-score curves at 0, ±1, ±2, and ± 3 SD for Chinese boys and girls from birth to 24 months

Length (cm)

Boys

Girls

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

L

M

S

-3SD

-2SD

-1SD

0SD

1SD

2SD

3SD

45

1.0000

2.54

0.1032

1.76

2.02

2.28

2.54

2.80

3.07

3.33

−0.5434

2.37

0.0928

1.83

1.99

2.17

2.37

2.61

2.89

3.21

46

1.0000

2.67

0.1028

1.85

2.12

2.40

2.67

2.95

3.22

3.50

−0.5303

2.56

0.0927

1.97

2.14

2.34

2.56

2.81

3.11

3.46

47

1.0000

2.81

0.1025

1.95

2.24

2.53

2.81

3.10

3.39

3.68

−0.5173

2.74

0.0927

2.12

2.30

2.51

2.74

3.02

3.33

3.70

48

1.0000

2.97

0.1021

2.06

2.36

2.66

2.97

3.27

3.57

3.88

−0.5041

2.93

0.0926

2.26

2.45

2.68

2.93

3.22

3.56

3.95

49

1.0000

3.15

0.1017

2.19

2.51

2.83

3.15

3.47

3.79

4.11

−0.4904

3.12

0.0926

2.41

2.62

2.85

3.12

3.44

3.79

4.21

50

1.0000

3.36

0.1012

2.34

2.68

3.02

3.36

3.70

4.04

4.38

−0.4757

3.34

0.0925

2.58

2.80

3.06

3.34

3.68

4.06

4.50

51

1.0000

3.61

0.1007

2.52

2.88

3.25

3.61

3.97

4.34

4.70

−0.4597

3.60

0.0924

2.77

3.02

3.29

3.60

3.96

4.37

4.84

52

1.0000

3.89

0.1001

2.72

3.11

3.50

3.89

4.28

4.67

5.06

−0.4434

3.88

0.0923

2.99

3.25

3.55

3.88

4.26

4.71

5.22

53

1.0000

4.18

0.0995

2.93

3.35

3.76

4.18

4.59

5.01

5.42

−0.4276

4.16

0.0922

3.20

3.48

3.80

4.16

4.57

5.04

5.58

54

1.0000

4.45

0.0990

3.13

3.57

4.01

4.45

4.89

5.33

5.77

−0.4126

4.42

0.0921

3.40

3.70

4.03

4.42

4.85

5.35

5.92

55

1.0000

4.71

0.0984

3.32

3.78

4.25

4.71

5.17

5.64

6.10

−0.3983

4.66

0.0920

3.58

3.90

4.26

4.66

5.12

5.64

6.24

56

1.0000

4.95

0.0978

3.50

3.99

4.47

4.95

5.44

5.92

6.41

−0.3841

4.90

0.0918

3.77

4.10

4.48

4.90

5.38

5.93

6.56

57

1.0000

5.21

0.0972

3.69

4.20

4.70

5.21

5.72

6.22

6.73

−0.3702

5.16

0.0917

3.98

4.33

4.72

5.16

5.67

6.24

6.90

58

1.0000

5.49

0.0966

3.90

4.43

4.96

5.49

6.02

6.55

7.08

−0.3572

5.46

0.0915

4.21

4.58

4.99

5.46

6.00

6.60

7.29

59

1.0000

5.81

0.0959

4.14

4.69

5.25

5.81

6.36

6.92

7.48

−0.3463

5.79

0.0912

4.46

4.85

5.29

5.79

6.35

6.99

7.72

60

1.0000

6.14

0.0952

4.39

4.97

5.56

6.14

6.73

7.31

7.90

−0.3376

6.11

0.0910

4.71

5.12

5.59

6.11

6.70

7.38

8.14

61

1.0000

6.48

0.0945

4.64

5.25

5.87

6.48

7.09

7.70

8.32

−0.3307

6.41

0.0907

4.94

5.38

5.86

6.41

7.03

7.73

8.53

62

1.0000

6.79

0.0938

4.88

5.52

6.16

6.79

7.43

8.07

8.71

−0.3252

6.69

0.0904

5.16

5.61

6.12

6.69

7.33

8.06

8.88

63

1.0000

7.09

0.0931

5.11

5.77

6.43

7.09

7.75

8.41

9.07

−0.3212

6.94

0.0901

5.35

5.82

6.35

6.94

7.60

8.35

9.21

64

1.0000

7.36

0.0925

5.32

6.00

6.68

7.36

8.05

8.73

9.41

−0.3184

7.19

0.0898

5.55

6.04

6.58

7.19

7.87

8.65

9.52

65

1.0000

7.63

0.0918

5.53

6.23

6.93

7.63

8.33

9.03

9.73

−0.3169

7.44

0.0894

5.75

6.25

6.81

7.44

8.14

8.94

9.84

66

1.0000

7.89

0.0912

5.73

6.45

7.17

7.89

8.61

9.33

10.05

−0.3170

7.69

0.0891

5.95

6.47

7.04

7.69

8.42

9.24

10.17

67

1.0000

8.14

0.0906

5.93

6.67

7.40

8.14

8.88

9.62

10.36

−0.3188

7.94

0.0887

6.15

6.68

7.27

7.94

8.68

9.53

10.48

68

1.0000

8.39

0.0900

6.13

6.88

7.64

8.39

9.15

9.90

10.66

−0.3223

8.18

0.0883

6.34

6.89

7.49

8.18

8.94

9.81

10.78

69

1.0000

8.64

0.0894

6.32

7.10

7.87

8.64

9.42

10.19

10.96

−0.3270

8.41

0.0879

6.53

7.09

7.71

8.41

9.19

10.08

11.08

70

1.0000

8.89

0.0889

6.52

7.31

8.10

8.89

9.68

10.47

11.26

−0.3328

8.63

0.0875

6.71

7.28

7.92

8.63

9.43

10.34

11.36

71

1.0000

9.13

0.0883

6.71

7.52

8.33

9.13

9.94

10.74

11.55

−0.3391

8.85

0.0871

6.89

7.47

8.12

8.85

9.67

10.59

11.63

72

1.0000

9.36

0.0878

6.90

7.72

8.54

9.36

10.19

11.01

11.83

−0.3458

9.06

0.0867

7.07

7.66

8.32

9.06

9.90

10.84

11.90

73

1.0000

9.59

0.0872

7.08

7.92

8.76

9.59

10.43

11.27

12.10

−0.3527

9.28

0.0863

7.25

7.85

8.53

9.28

10.13

11.09

12.18

74

1.0000

9.82

0.0867

7.26

8.12

8.97

9.82

10.67

11.52

12.37

−0.3597

9.50

0.0858

7.43

8.04

8.73

9.50

10.37

11.34

12.45

75

1.0000

10.04

0.0861

7.44

8.31

9.17

10.04

10.90

11.77

12.63

−0.3667

9.72

0.0854

7.61

8.23

8.93

9.72

10.60

11.59

12.72

76

1.0000

10.26

0.0856

7.62

8.50

9.38

10.26

11.13

12.01

12.89

−0.3737

9.93

0.0850

7.78

8.42

9.13

9.93

10.83

11.84

12.98

77

1.0000

10.47

0.0851

7.80

8.69

9.58

10.47

11.36

12.25

13.14

−0.3806

10.14

0.0846

7.96

8.60

9.33

10.14

11.05

12.07

13.24

78

1.0000

10.68

0.0846

7.97

8.87

9.78

10.68

11.58

12.49

13.39

−0.3872

10.34

0.0842

8.13

8.78

9.52

10.34

11.26

12.30

13.48

79

1.0000

10.88

0.0841

8.14

9.05

9.97

10.88

11.80

12.71

13.63

−0.3933

10.53

0.0837

8.29

8.96

9.70

10.53

11.47

12.53

13.72

80

1.0000

11.07

0.0836

8.30

9.22

10.15

11.07

12.00

12.93

13.85

−0.3988

10.72

0.0834

8.45

9.12

9.88

10.72

11.67

12.74

13.95

81

1.0000

11.26

0.0832

8.45

9.39

10.32

11.26

12.20

13.13

14.07

−0.4036

10.91

0.0830

8.60

9.29

10.05

10.91

11.87

12.95

14.18

82

1.0000

11.44

0.0828

8.60

9.55

10.49

11.44

12.39

13.33

14.28

−0.4076

11.09

0.0826

8.76

9.45

10.22

11.09

12.06

13.16

14.40

83

1.0000

11.62

0.0823

8.75

9.71

10.67

11.62

12.58

13.54

14.49

−0.4109

11.28

0.0822

8.92

9.62

10.40

11.28

12.26

13.37

14.63

84

1.0000

11.81

0.0819

8.91

9.87

10.84

11.81

12.78

13.74

14.71

−0.4134

11.47

0.0819

9.08

9.79

10.58

11.47

12.47

13.59

14.86

85

1.0000

12.00

0.0815

9.07

10.05

11.03

12.00

12.98

13.96

14.94

−0.4149

11.68

0.0815

9.25

9.98

10.78

11.68

12.69

13.83

15.11

86

1.0000

12.21

0.0810

9.24

10.23

11.22

12.21

13.20

14.19

15.18

−0.4151

11.90

0.0811

9.44

10.17

10.99

11.90

12.92

14.08

15.38

87

1.0000

12.43

0.0806

9.42

10.42

11.42

12.43

13.43

14.43

15.43

−0.4137

12.13

0.0807

9.63

10.38

11.21

12.13

13.17

14.34

15.66

88

1.0000

12.66

0.0801

9.62

10.63

11.64

12.66

13.67

14.69

15.70

−0.4105

12.38

0.0803

9.84

10.60

11.44

12.38

13.44

14.62

15.96

89

1.0000

12.91

0.0797

9.82

10.85

11.88

12.91

13.94

14.96

15.99

−0.4056

12.65

0.0799

10.06

10.83

11.69

12.65

13.72

14.92

16.28

90

1.0000

13.17

0.0792

10.04

11.09

12.13

13.17

14.22

15.26

16.30

−0.3987

12.92

0.0796

10.28

11.07

11.94

12.92

14.01

15.23

16.60

91

1.0000

13.46

0.0787

10.28

11.34

12.40

13.46

14.52

15.58

16.64

−0.3901

13.19

0.0792

10.51

11.31

12.20

13.19

14.30

15.54

16.93

92

1.0000

13.75

0.0782

10.53

11.60

12.68

13.75

14.83

15.91

16.98

−0.3797

13.47

0.0789

10.74

11.56

12.47

13.47

14.60

15.86

17.27

93

1.0000

14.06

0.0778

10.78

11.87

12.97

14.06

15.15

16.25

17.34

−0.3677

13.75

0.0786

10.97

11.80

12.73

13.75

14.89

16.17

17.60

94

1.0000

14.37

0.0773

11.04

12.15

13.26

14.37

15.48

16.59

17.71

−0.3543

14.03

0.0783

11.20

12.05

12.99

14.03

15.19

16.48

17.93

95

1.0000

14.68

0.0769

11.30

12.43

13.56

14.68

15.81

16.94

18.07

−0.3398

14.30

0.0780

11.42

12.29

13.24

14.30

15.48

16.79

18.25

96

1.0000

15.00

0.0764

11.56

12.71

13.85

15.00

16.15

17.29

18.44

−0.3243

14.57

0.0777

11.64

12.52

13.50

14.57

15.77

17.10

18.57

97

1.0000

15.32

0.0760

11.82

12.99

14.15

15.32

16.48

17.65

18.81

−0.3081

14.84

0.0775

11.86

12.76

13.75

14.84

16.05

17.39

18.89

98

1.0000

15.63

0.0756

12.09

13.27

14.45

15.63

16.82

18.00

19.18

−0.2914

15.10

0.0772

12.07

12.99

13.99

15.10

16.33

17.69

19.20

99

1.0000

15.95

0.0751

12.36

13.56

14.75

15.95

17.15

18.35

19.55

−0.2744

15.37

0.0769

12.29

13.22

14.24

15.37

16.61

17.98

19.51

100

1.0000

16.27

0.0747

12.62

13.84

15.06

16.27

17.49

18.70

19.92

−0.2575

15.63

0.0767

12.50

13.45

14.49

15.63

16.89

18.28

19.81

Fig. 3
Fig. 3

Comparison of weight-for-length z-score curves from China 2015 data with the WHO standards and Chinese references from 2005 data in boys and girls

For z-score of − 2 (cutoff for wasting definition) in boys, weight was ~ 0.29 kg higher (range 0.003–0.94 kg) than the WHO standard at length > 64 cm; between length 45–63 cm, it was 0.08 kg lower (ranged 0.02 to − 0.17) (Fig. 3). In Chinese girls, the weight-for-length values at z-score of − 2 were on average 0.44 kg heavier (ranging 0.001 to 0.85 kg) than the WHO standards for length > 49 cm. For z-score of 2 (cutoff for overweight definition), compared to the WHO standards, weight was on average 0.39 kg higher (range 0.04 to 0.75 kg) in Chinese boys, and 0.34 kg higher (range 0.06 to 0.64 kg) in Chinese girls for the length > 50 cm. Similarly, for z-score of 3, weight-for-length was on average 0.16 kg higher (range − 0.11to 0.36 kg) in Chinese boys, and was 0.30 kg higher (range 0.00 to 0.64 kg) at most length (49 cm to 95 cm) in Chinese girls than the WHO standards.

Compared to cross-sectional 2005 growth references for China, the median weight-for-length was on average 0.31 kg-cm higher (range 0.03–1.00 kg-cm) in boys and 0.28 (range 0.02–0.56) kg-cm higher in girls across length in this study (Fig. 3).

The difference between our raw data and WHO standards

The numbers of anthropometric measurements used for generating smoothed growth curves was shown in Additional file 1: Tables S2 and S3. This study measured the children at 7 targeted ages (42 days, 3, 6, 9, 12, 18 and 24 months), but in fact provided adequate monthly numbers in the first 12 months (Additional file 1: Tables S2 and S3). In addition to above comparison of the LMS-method-fitted smoothing curves, we also presented the 3rd, 10th, 50th, 90th and 97th percentiles of growth measures by age in both boys (Additional file 1: Table S4) and girls (Additional file 1: Table S5). Compared to the corresponding 2006 WHO percentile standards, the 3rd, 10th, 50th, 90th and 97th percentiles (across the ages evaluated in this study from 0 to 2 years) for length, weight, and BMI (Additional file 1: Table S4 for boys and Additional file 1: Table S5 for girls) were consistently higher in healthy Chinese boys (Additional file 1: Table S6) and girls (Additional file 1: Table S7) in 2015. For example, the median lengths from 0 to 2 years were 50.0–89.5 cm in boys (Additional file 1: Table S4), which were 0.1–3.1 cm taller than the WHO percentile standards (Additional file 1: Table S6). The differences compared to WHO standards also were present for weight by length in both boys and girls (Additional file 1: Tables S8 and S9). This indicates the robust of our results.

Discussion

This report of growth measures is based on a large cohort of children (n = 4251) from six recent birth cohorts from China. Growth references from this study represent normal growth of today’s Chinese children from birth to 24 months by using the multicenter data collected recently (from 2012 to 2015). Compared with the WHO standards (collected more than 10 years ago from mid-1997 to end of 2003) and the current China references (collected 10-years ago in late 2005), the median values of length-, weight-, and BMI-for-age reported here were all higher across the ages from 0 to 2 years, and also for median head circumference-for-age except for boys in our study compared to the 2005 references for China. The weight-for-length in our study was also slightly higher at most times in both boys and girls. The magnitude of differences between the WHO standards and the current large cohort (assessed in 2015) was larger than the magnitude of differences previously reported compared to the outdated 2005 references for China. Our report provides improved references for evaluating growth of children aged 0–24 months in modern China.

The height- and weight-for-age values were higher in our longitudinal cohort assessed in five cities of China (Shanghai, Ma’anshan Anhui, Wuhan, Jiangsu, and Guangzhou) than in the cohort based on a cross-sectional study in nine cities of China (Beijing, Shanghai, Harbin, Xi’an, Nanjing, Wuhan, Guangzhou, Fuzhou, and Kunming) [3]. This could be a secular trend. The CBCC cohorts recruited pregnant women in provincial or large tertiary maternity and child hospitals. Most mothers had high education (college or higher), maternal smoking was rare, and the living standard were relatively high. Thus, the growth data in this study may reflect infant growth patterns under near-optimal circumstances. Since our data were acquired recently (10 years since 2005), the higher length and weight may also reflect an ongoing secular trend [4]. The WHO data suggest that secular trend may depend on where the cohort was acquired: the predicted adult height from the child’s length at 2 years suggested there would be no parent-offspring difference in Norway and the United States (i.e., no increase due to a secular trend), but the predicted adult height was much larger than mid-parental height for the other four countries (Brazil, Ghana, India and Oman). [15] Based on the taller height reported here for ages 0 to 24 months than the 2005 China data, we expect a secular trend (i.e., we predict that average adulthood the height of the children in China will exceed the average height of their parents). While China has undergone dramatic progress in economic and social development, the differences still exist between urban and rural areas, different ethnics, and different social economic. The growth pattern observed in this study may reflect infant growth patterns under more optimal circumstances.

Some studies have found that some child population might have their own growth pattern [16], and our study confirmed that Chinese children may be one of them [3, 17, 18]. The difference in values for height-, weight- and BMI-for-age, weight-for-length, and head circumference in this report in comparison to the WHO standards suggests an interesting country difference, and adds to previous comparison that have been summarized in a recent review [19]. Based on studies from both longitudinal and cross-sectional designs, this review concluded that the WHO standards for height and weight “… endorsed slenderness in the midst of an obesity epidemic” and for head circumference were underestimates (and “… would put many children at risk for misdiagnosis of macrocephaly and microcephaly”). Healthy children in some countries are classified (perhaps inappropriately) as “stunted” [16]. In opposite of findings from some countries (overestimating stunting) [16], overall, our study confirmed that the values of growth measures were higher for the key z-score cutoffs in Chinese children in comparison with WHO growth standards [3, 5].

Our references provide the potential cutoffs for evaluating child growth in a population (like in modern China), where children are the center of attention in the family and are growing under favorable environments. Length has been widely used in early detection of stunting, while weight is commonly used as a measure responsive to short-term influences [20]. Head circumference is then the next most-used measure in clinical settings. To reflect the growth centile (position) of a Chinese child in local population, conditioned on age and sex, the Chinese growth standards need to be considered. It may help identify the infants who suffer from poor and modifiable conditions, and thus target those who may benefit most from intervention. In this study, while another term was considered (“growth pattern”), the term “growth reference” was used to maintain consistency with the term used in other publications about Chinese cohorts and to contrast to the term “growth standard” used for the WHO cohort.

One characteristic of this study (the large-scale multicenter prospective birth cohort design) allows us to obtain data on pre- and perinatal risk factors including GDM, chronic hypertension, pre-eclampsia and preterm status. Based on this strength, we could exclude affected mother-infant pairs cases at risk for abnormal patterns of child growth. In this study, the difference of mean paternal age among the three groups of children (mothers with GDM, born preterm, and healthy children) is interesting. Older fathers have more de novo mutations in DNA, and this probably contributes to growth in some cases [21]. Another strength of this study is the longitudinal rather than cross-sectional design. Additional longitudinal analysis [22, 23] of these longitudinal data could better capture and describe the tempo of growth, but due to space limitations will be presented elsewhere. Also, in this sample the educational level of mothers was high, and few of the mothers smoked, so the children lived in advantaged condition, and approach the criteria used for establishing the WHO standards (reflecting how children should grow). Therefore, the data here may reflect growth in near-optimal conditions in China, and provide a growth pattern for contemporary Chinese children.

On the other hand, one limitation of this study is that in some cases head circumference at birth was not measured, and some of children were just followed up to 12 months, which reduced the sample size for this measurement. However, our sample size is still larger than the sample sizes in similar longitudinal birth cohort studies conducted in other countries. We have also performed sensitivity analysis to summary the 3rd, 10th, 50th, 90th and 97th percentiles of all growth measures in infant who had all observations up to 24 months (i.e., without missing observations) and the results were similar to those from all observations (data not shown). Thus, the missing data should be “at random” [9] Also, the birth measures obtained from medical records may not be ideal despite of the high number of the participating hospitals (which were all provincial or large tertiary maternity and child hospitals). Thirdly, this was a convenience sample without specific entry criteria as in the WHO study.

Conclusions

The growth curves in this study represent the growth pattern of today’s normal Chinese children, and may provide references for evaluation of the individual growth status of children growing up in modern China.

Abbreviations

ART: 

Assisted reproductive technologies

CBCC: 

China Birth Cohort Consortium

GDM: 

Gestational diabetes mellitus

IADPSG: 

International Association of Diabetes and Pregnancy Study Groups

MGRS: 

Multicenter Growth Reference Study

WHO: 

World Health Organization

Declarations

Acknowledgements

We thank Dr. James Swanson, Dr. Michael Hermanussen and Dr. Zhong-Cheng Luo for their intensive reviews and insightful comments on this manuscript.

Funding

This work was funded by the Gates Foundation Healthy Birth, Growth & Development knowledge integration (HBGDki) project (No. OPP1153191). Dr. F. Ouyang was also supported by grants from National Natural Science Foundation of China (grant numbers 81673178; 81372954) and Coordinated Research Project E43032 from International Atomic Energy Agency (IAEA). The funders were not involved in the study design, data collection, analysis, and interpretation, or manuscript preparation.

Availability of data and materials

This study is based on six birth cohorts. The datasets generated and/or analysed during the current study are not publicly available due to that some of the cohort studies are still ongoing but are available from the corresponding author on reasonable request.

Authors’ contributions

FO conceptualized, designed and conducted this study, performed the statistical analysis, and drafted the manuscript. JZ conceptualized this study, and critically reviewed the manuscript. All authors (JZ, FO, FJ, FT, SX, YX, and XQ) took responsibility for one cohort, and critically reviewed the manuscript. All authors read and approved the final manuscript as submitted.

Ethics approval and consent to participate

This project was approved by the institutional review board (IRB) of Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine (Approval number: XHEC-C-2017-060). Written consent to participate was obtained from participants in each cohort study. For this pooled analysis, the need for consent was waived by IRB of Xinhua Hospital.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Ministry of Education and Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China
(2)
Department of Developmental and Behavioral Pediatrics, Shanghai Pediatric Transitional Institution, Shanghai Children’s Medical Center affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
(3)
School of Public Health, Anhui Medical University, Hefei, 230032, China
(4)
Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China
(5)
School of Public Health, Nanjing Medical University, Nanjing, 211166, China
(6)
Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, 510000, China

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Copyright

© The Author(s). 2018

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