INTRODUCTION: The growing years are paramount for bone growth and mineral accrual. Children with long-term neurological condition (LTNC) have multiple risk factors for poor bone health and fragility fractures. In Singapore, this has not been studied systematically. Therefore, we aimed to evaluate the risk factors associated with fragility fractures in children with LTNC. METHODS: In this study, the search for fragility fractures was done by a retrospective review of patients with LTNC on follow-up in the paediatric neurology clinic and patients who presented with fracture to the paediatric orthopaedic clinic. Information on patients' demographics, medical history, intervention, biochemical bone markers and fracture history was collected. RESULTS: In a tertiary clinic population of 136 patients with LTNC, 65% were dependent on mobility (Gross Motor Function Classification System [GMFCS] V), 60% were underweight and 60% were fed via gastrostomy or nasogastric tube, or were on oral pureed diet. Furthermore, 60% were on anticonvulsants. The fracture rate was 3% in this population and was associated with low-impact activities such as transfer and dressing. Only 7.4% and 33% of the patients had undergone measurements of vitamin D and calcium levels, respectively. CONCLUSION The local prevalence of fragility fractures in children with LTNC on follow-up at the neurology clinic was found to be 3%. Risk factors identified were limited ambulation and compromised nutritional status associated with feeding difficulty. Recommendations to optimise bone health in children with LTNC were made. These include promoting weight-bearing activities, looking out for underweight children, avoiding vitamin D deficiency and ensuring adequate calcium intake.
Humans ; Child ; Bone Density ; Calcium ; Thinness/epidemiology* ; Fractures, Bone/etiology* ; Risk Factors

Objective: To compare the application of China growth standard for children under 7 years of age (China standards) and World Health Organization child growth standards (WHO standards) in evaluating the prevalence of malnutrition in children aged 0-<6 years in China. Methods: The research data came from the national special program for science & technology basic resources investigation of China, named "2019-2021 survey and application of China's nutrition and health system for children aged 0-18 years". Multi-stage stratified random sampling was used to recruit 28 districts (regions) in 14 provinces, autonomous regions or municipalities across the country. Children (n=38 848) were physically measured and questionnaires were conducted in the guardians of the children. The indicators of stunting, underweight, wasting, overweight and obesity were evaluated by China standards and WHO standards respectively. Chi-square test was used to comparing the prevalence of each nutritional status between the two standards, as well as the comparison between the two standards by gender and age. Results: Among the 38 848 children, 19 650 were boys (50.6%) and 19 198 were girls (49.4%), 19 480 urban children (50.1%) and 19 368 rural children (49.9%). The stunting, underweight and wasting cases in the study population were 2 090 children (5.4%), 1 354 children (3.5%) and 1 276 children (3.3%) according to the China standards, and 1 474 children (3.8%), 701 children (1.8%) and 824 children (2.1%) according to the WHO standards, respectively; the above rates according to the China standards were slightly higher than those to the WHO standards (χ²=111.59, 213.14, and 99.99, all P<0.001). The overweight and obesity cases in the study population were 2 186 children (5.6%) and 1 153 children (3.0%) according to the China standards, and 2 210 children (5.7%) and 1 186 children (3.1%) according to the WHO standards, with no statistically significant differences (χ²=0.14 and 0.48, P=0.709 and 0.488, respectively). Compared to the results based on WHO standards, the China standards showed a lower prevalence of overweight and obesity in boys (χ²=14.95 and 5.85, P<0.001 and =0.016, respectively), and higher prevalence of overweight in girls (χ²=12.60, P<0.001); but there was no statistically significant differences in girls' obesity prevalence between the two standards (χ²=2.62, P=0.106). Conclusions: In general, the prevalence of malnutrition among children aged 0-<6 years based on China standards is slightly higher than that on WHO standards. To evaluate the nutritional status of children, it is advisable to select appropriate child growth standards based on work requirements, norms or research objectives.
Male ; Female ; Child ; Humans ; Child, Preschool ; Nutritional Status ; Overweight/epidemiology* ; Thinness/epidemiology* ; Obesity/epidemiology* ; Malnutrition/epidemiology* ; Growth Disorders/epidemiology* ; China/epidemiology* ; Prevalence

Objective: To analyze the incidence of preterm birth based on pre-pregnancy body mass index (BMI) stratification and explore the associated factors of preterm birth among pregnant women at different BMI stratifications. Methods: From February 2018 to December 2020, pregnant women who participated in China Birth Cohort Study (CBCS) and gave birth at Beijing Obstetrics and Gynecology Hospital were enrolled as the study subjects. Electronic Data Capture System and standard structured questionnaires were used to collect data related to pre-pregnancy, pregnancy, and delivery for pregnant women. Pregnant women were divided into the low-weight group, normal-weight group and overweight group based on their pre-pregnancy BMI. A Cox proportional hazards model was used to analyze the associated factors of preterm birth among pregnant women with different BMI before pregnancy. Results: A total of 27 195 singleton pregnant women were included, with a preterm birth rate of 5.08% (1 381/27 195). The preterm birth rates in the low-weight group, normal-weight group and overweight group were 4.29% (138/3 219), 4.63% (852/18 390) and 7.00% (391/5 586) respectively (P<0.001). After adjusting for relevant factors, the Cox proportional hazards model showed that the risk of preterm birth in the overweight group was 1.457 times higher than that in the normal-weight group (95%CI: 1.292-1.643). Preeclampsia-eclampsia (HR=2.701, 95%CI: 1.318-5.537) was the associated factor for preterm birth in the low-weight group. Advanced maternal age (HR=1.232, 95%CI: 1.054-1.441), history of preterm birth (HR=4.647, 95%CI: 3.314-6.515), vaginal bleeding in early pregnancy (HR=1.613, 95%CI: 1.380-1.884), and preeclampsia-eclampsia (HR=3.553, 95%CI: 2.866-4.404) were associated factors for preterm birth in the normal-weight group. Advanced maternal age (HR=1.473, 95%CI: 1.193-1.818), history of preterm birth (HR=3.209, 95%CI: 1.960-5.253), vaginal bleeding in early pregnancy (HR=1.636, 95%CI: 1.301-2.058), preeclampsia-eclampsia (HR=2.873, 95%CI:2.265-3.643), and pre-gestational diabetes mellitus (HR=1.867, 95%CI: 1.283-2.717) were associated factors for preterm birth in the overweight group. Conclusion: Pre-pregnancy overweight is an associated factor for preterm birth, and there are significant differences in the associated factors of preterm birth among pregnant women with different BMI before pregnancy.
Pregnancy ; Infant, Newborn ; Female ; Humans ; Body Mass Index ; Overweight/epidemiology* ; Premature Birth/epidemiology* ; Pre-Eclampsia/epidemiology* ; Cohort Studies ; Eclampsia ; Incidence ; Risk Factors ; Thinness/epidemiology*

Objective: To evaluate the association between pre-and post-diagnosis body mass index (BMI) and risk of colorectal cancer (CRC) death. Methods: The cohort consisted of 3, 057 CRC patients from Shanghai who were diagnosed from Jan. 1, 2009 to Dec. 31, 2011 and aged from 20 to 74 years. The pre- and post-diagnosis BMI and clinical and lifestyle factors were collected at baseline. Death information was collected using record linkage with the Shanghai Cancer Registry and telephone confirmation during follow-up by the end of 2019. The Cox proportional regression model was used to estimate HR with 95% CI. Results: Analysis by multivariable Cox model showed no association between pre-diagnosis BMI and death risk in both male and female patients. Male patients with a post-diagnosis underweight BMI had an elevated risk of death compared to those in normal weight (HR=1.69, 95% CI: 1.21-2.37), especially in early stage cases. Overweight patients (HR=0.74, 95% CI: 0.61-0.89) and patients with obesity class Ⅰ (HR=0.63, 95% CI: 0.45-0.89)had better survival with decreased risks of death, especially in advanced stage cases. The decreased death risk in patients with obesity class Ⅱ was not significant (HR=0.57, 95% CI: 0.24-1.39). The P(trend) value for decreased risk of death with increased BMI in female patients was statistically significant (P<0.001), and the overweight and obesity class Ⅰ categories had better survival in advanced stage(HR(overweight)=0.62, 95% CI: 0.42-0.93; HR(obesity class Ⅰ)=0.39, 95% CI: 0.16-0.98). Both male and female patients with post-diagnosis BMI loss >2.0 kg/m(2) had an increased death risk when compared with those with stable BMI (change≤1.0 kg/m(2)) between pre- and post-diagnosis. BMI gain after diagnosis did not change death risk. Conclusions: Post-diagnosis BMI in the overweight or obesity class Ⅰ groups might be conducive to prolonging male CRC patients' survival, while underweight might result in poor prognosis. Keeping weight and avoiding excessive weight loss should be suggested for all CRC patients after diagnosis.
Female ; Humans ; Male ; Body Mass Index ; China/epidemiology* ; Colorectal Neoplasms/complications* ; Obesity/complications* ; Overweight/complications* ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Thinness/complications* ; Young Adult ; Adult ; Middle Aged ; Aged

Objective: To evaluate the association between pre-and post-diagnosis body mass index (BMI) and risk of colorectal cancer (CRC) death. Methods: The cohort consisted of 3, 057 CRC patients from Shanghai who were diagnosed from Jan. 1, 2009 to Dec. 31, 2011 and aged from 20 to 74 years. The pre- and post-diagnosis BMI and clinical and lifestyle factors were collected at baseline. Death information was collected using record linkage with the Shanghai Cancer Registry and telephone confirmation during follow-up by the end of 2019. The Cox proportional regression model was used to estimate HR with 95% CI. Results: Analysis by multivariable Cox model showed no association between pre-diagnosis BMI and death risk in both male and female patients. Male patients with a post-diagnosis underweight BMI had an elevated risk of death compared to those in normal weight (HR=1.69, 95% CI: 1.21-2.37), especially in early stage cases. Overweight patients (HR=0.74, 95% CI: 0.61-0.89) and patients with obesity class Ⅰ (HR=0.63, 95% CI: 0.45-0.89)had better survival with decreased risks of death, especially in advanced stage cases. The decreased death risk in patients with obesity class Ⅱ was not significant (HR=0.57, 95% CI: 0.24-1.39). The P(trend) value for decreased risk of death with increased BMI in female patients was statistically significant (P<0.001), and the overweight and obesity class Ⅰ categories had better survival in advanced stage(HR(overweight)=0.62, 95% CI: 0.42-0.93; HR(obesity class Ⅰ)=0.39, 95% CI: 0.16-0.98). Both male and female patients with post-diagnosis BMI loss >2.0 kg/m(2) had an increased death risk when compared with those with stable BMI (change≤1.0 kg/m(2)) between pre- and post-diagnosis. BMI gain after diagnosis did not change death risk. Conclusions: Post-diagnosis BMI in the overweight or obesity class Ⅰ groups might be conducive to prolonging male CRC patients' survival, while underweight might result in poor prognosis. Keeping weight and avoiding excessive weight loss should be suggested for all CRC patients after diagnosis.
Female ; Humans ; Male ; Body Mass Index ; China/epidemiology* ; Colorectal Neoplasms/complications* ; Obesity/complications* ; Overweight/complications* ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Thinness/complications* ; Young Adult ; Adult ; Middle Aged ; Aged

Objective: To explore the association between weight gain during the first half of pregnancy and the risk of hypertension disorder of pregnancy (HDP). Methods: This prospective cohort study recruited singleton pregnant women in the first trimester from November 2016 to March 2019 at 19 community hospitals in Tianjin. According to pre-pregnancy body mass index (BMI), the cohort was divided into 3 groups: underweight(BMI<18.5 kg/m²), normal-weight(18.5-24.9 kg/m²), and overweight/obese(≥25.0 kg/m²). The basic information of the participants was gathered through questionnaires, and the height, weight, and blood pressure of the participants were measured along with routine pregnancy examinations. The rate of gestational weight gain (rGWG) in the 3 periods (0-13⁺⁶, 14⁺⁰-20⁺⁶, and 0-20⁺⁶ weeks) of the participants was calculated. To observe the occurrence of HDP, the participants were followed up to 42 days postpartum. Using a generalized linear model, the association between rGWG at the 3 periods during the first half of pregnancy and HDP after 20 weeks of gestation was evaluated. Results: A total of 9 805 pregnant women were finally included, with the age of (30.6±3.8) years old, 9 418 (96.1%) Han ethnicity, and 6 845 (69.8%) primipara. There were 1 184 (12.1%), 6 831 (69.7%) and 1 790 (18.3%) participants in the underweight, normal-weight, and overweight/obese groups. Five hundreds and eight pregnant women were diagnosed with HDP (5.2%). The incidences of HDP were 1.8% (21/1 184), 3.9% (269/6 831), and 12.2% (218/1 790), respectively, in underweight, normal-weight, and overweight/obese groups. Adjusted for age, pre-pregnancy BMI, primipara, and family history of hypertension, women in the entire cohort with rGWG ≥ 0.18 kg/week before 13⁺⁶ weeks of pregnancy had a 28% higher HDP risk than those with rGWG ≤ 0.00 kg/week (RR=1.28, 95%CI 1.04-1.55, P=0.015), and the risk of HDP was increased by 39% in the overweight/obese group (RR=1.39, 95%CI 1.04-1.85, P=0.026), while no correlation was found between rGWG and HDP in underweight and normal-weight pregnant women (P>0.05). Weight gain during 14⁺⁰-20⁺⁶ weeks of pregnancy in any group was not related to the risk of HDP (P>0.05).In the entire cohort, compared to rGWG ≤0.14 kg/week, rGWG≥0.28 kg/week prior to 20⁺⁶ weeks increased HDP risk by 36% (RR=1.36, 95%CI 1.11-1.67, P=0.003). Normal-weight pregnant women with rGWG≥0.29 kg/week faced a 46% higher risk of HDP than those with rGWG≤0.15 kg/week (RR=1.46, 95%CI 1.11-1.93, P=0.008).In the overweight/obese group, excessive weight gain before 20⁺⁶ weeks seemed to increased risk of HDP, but the difference was not statistically significant (RR=1.35,95%CI 0.99-1.85, P=0.059), while the connection was nonexistent in underweight women. Conclusions: Except for pre-pregnancy underweight women, excessive weight gain during the first half of pregnancy is associated with increased risk of HDP among pregnant women.
Female ; Pregnancy ; Humans ; Infant, Newborn ; Adult ; Overweight/complications* ; Thinness/epidemiology* ; Prospective Studies ; Risk Factors ; Weight Gain ; Body Mass Index ; Obesity/complications* ; Hypertension, Pregnancy-Induced/etiology* ; Cohort Studies ; Pregnancy Complications

Objective: To evaluate the association of lead exposure with stunting and underweight among children aged 3-5 years in China. Methods: Data was collected from China National Human Biomonitoring (CNHBM) between January 2017 and December 2018. A total of 3 554 children aged 3-5 years were included. Demographic characteristic, lifestyle and nutritional status were collected through questionnaires. Height and weight were measured by standardized method. Stunting and underweight status were determined by calculating height for age Z-score and weight for age Z-score. Blood and urine samples were collected to detect the concentrations of blood lead, urinary lead and urinary creatinine. Children were stratified into 4 groups (Q₁ to Q₄) by quartiles of blood lead level and corrected urinary lead level, respectively. Complex sampling logistic regression models were applied to evaluate the association of the blood lead level, urinary lead level with stunting and underweight. Results: Among 3 554 children, the age was (4.09±1.06) years, of which 1 779 (80.64%) were female and 1 948 (55.84%) were urban residents. The prevalence of stunting and wasting was 7.34% and 2.96%, respectively. The M (Q₁, Q₃) for blood lead levels and urinary lead levels in children was 17.49 (12.80, 24.71) μg/L, 1.20 (0.61, 2.14) μg/g Cr, respectively. After adjusting for confounding factors, compared with the lowest blood lead concentration group Q₁, the risk of stunting gradually increased in the Q₃ and Q₄ group (P_trend=0.010), with OR (95%CI) values of 1.40 (0.80-2.46) and 1.80 (1.07-3.04), respectively. Compared with the lowest urinary lead concentration group Q₁, the risk of stunting still increased in the Q₃ and Q₄ group (P_trend=0.012), with OR (95%CI) values of 1.69 (1.01-2.84) and 1.79 (1.05-3.06), respectively. The correlation between the lead exposure and underweight was not statistically significant (P>0.05). Conclusion: Lead exposure is positively associated with the risk of stunting among children aged 3-5 years in China.
Child ; Female ; Humans ; Infant ; Male ; Lead ; Thinness/epidemiology* ; Growth Disorders/epidemiology* ; Body Height ; Nutritional Status ; Prevalence ; China/epidemiology*

Objective: To examine the independent and combined effects of pre-pregnancy BMI and gestational diabetes (GDM) on early adiposity rebound (AR) timing in children. Methods: Based on the "Ma'anshan Birth Cohort Study", 2 896 eligible maternal and infant pairs were recruited. In the cohort, we collected pre-pregnancy height, weight, 24 to 28 weeks GDM diagnosis, follow-up at 42 days, three months, six months, nine months of age, and every six months after one year of age, and continuously followed up to 6 years old, and obtained the child's length/height, weight, and other data. The intensity of the association between pre-pregnancy BMI, GDM, and early AR timing was analyzed by the multivariate logistic regression model. Multiplication and additive models were used to analyze how pre-pregnancy BMI and GDM influenced early AR timing in children. Results: The prevalence of underweight, average weight, overweight, and obesity before pregnancy were 23.2% (672), 66.4% (1 923), 8.7% (251), and 1.7% (50). The prevalence of GDM was 12.4%. We found that 39.3% of children had AR, and the average age at AR was (4.38±1.08). The results of multifactorial logistic regression analysis showed that pre-pregnancy overweight (OR=1.67,95%CI:1.27-2.19), pre-pregnancy obesity (OR=3.05,95%CI:1.66-5.56), and maternal GDM (OR=1.40,95%CI:1.11-1.76) were risk factors for early AR timing in children. In contrast, pre-pregnancy underweight (OR=0.60,95%CI:0.49-0.73) was a protective factor for early AR timing in children. Compared with the different effects of pre-pregnancy overweight/obesity and maternal GDM alone, the combined effect caused a higher risk of early AR timing in children, with OR values (95%CI) were 2.03 (1.20-3.44), 3.43 (1.06-11.12), respectively. The multiplication and additive models showed no interaction between pre-pregnancy BMI and GDM-influenced early AR timing in children. Conclusion: Higher pre-pregnancy BMI and maternal GDM are the independent risk factors for the early AR timing in children, and the co-occurrence of the two is higher risks, but there was no statistical interaction.
Child ; Infant ; Female ; Pregnancy ; Humans ; Adiposity ; Diabetes, Gestational/epidemiology* ; Overweight/epidemiology* ; Thinness ; Cohort Studies ; Body Mass Index ; Obesity

Objective: Nutrition is closely related to the health of the elderly population. This study aimed to provide a comprehensive picture of the nutrition status of elderly Chinese and its related dietary, geographical, and socioeconomic factors. Methods: A total of 13,987 ≥ 60-year-old persons from the 2010-2013 Chinese National Nutrition and Health Survey were included to evaluate various aspects of malnutrition, including underweight, overweight or obesity, and micronutrient inadequacy. Results: Overall, the prevalence of obesity, overweight, and underweight was 12.4%, 34.8%, and 5.7%, respectively, with disparities both geographically and socioeconomically. The prevalence of underweight was higher among the older old (≥ 75 years), rural residents and those with low income, with low education status, and residing in undeveloped West areas. More than 75% of the elderly do not meet the Dietary Reference Intakes for vitamins A, B Conclusions Obesity epidemic, inadequacy of micronutrient intake, and high prevalence of underweight and anemia in susceptible older people are the major nutrition challenges for the rapidly aging population in China.
Age Factors ; Aged ; Aged, 80 and over ; China/epidemiology* ; Cross-Sectional Studies ; Diet/statistics & numerical data* ; Female ; Health Surveys ; Humans ; Male ; Malnutrition/etiology* ; Micronutrients/deficiency* ; Middle Aged ; Nutritional Status ; Overweight/etiology* ; Risk Factors ; Socioeconomic Factors ; Thinness/etiology*

Objective: To investigate the association between maternal pre-pregnant body mass index and gestational weight gain, as well as their interaction on neonatal birthweight. Methods: We built a cohort in Anqing Municipal Hospital from January 2014 to March 2015, enrolling pregnant women who decided to give birth in this hospital. All women were asked to fill a questionnaire for basic information collection. Medical information of both pregnant women and their newborns were obtained through electronic medical record. Chi-square analysis, multinomial logistic regression, multiplicative and additive interaction methods were used to analyze the association between pre-pregnant body mass index and gestational weight gain as well as their interactions on birth weight of the neonates. Results: A total of 2 881 pregnant women were included in this study. Of the 2 881 newborns, 359 (12.46%) were small for gestational age (SGA) and 273 (9.48%) were large for gestational age (LGA). After adjusting the possible confounding factors, results from the multinomial logistic regression showed that pre-pregnancy underweight women were more possible to deliver SGA (aRR=1.33, 95%CI: 1.02-1.73). If the gestational weight gain was below the recommended criteria, the risk of SGA (aRR=1.64, 95%CI: 1.23-2.19) might increase. Pre-pregnancy overweight/obese could increase the risk of being LGA (aRR=1.86, 95%CI: 1.33-2.60). Maternal gestational weight gain above the recommendation level was associated with higher rates of LGA (aRR=2.03, 95%CI: 1.49-2.78). Results from the interaction analysis showed that there appeared no significant interaction between pre-pregnancy BMI and gestational weight on birthweight. Conclusion: Pre-pregnancy body mass index and gestational weight gain were independently associated with neonatal birthweight while pre-pregnancy BMI and gestational weight gain did not present interaction on birthweight.
Birth Weight ; Body Mass Index ; Body Weight ; China/epidemiology* ; Cohort Studies ; Female ; Gestational Weight Gain ; Humans ; Infant, Newborn ; Infant, Small for Gestational Age ; Logistic Models ; Obesity/epidemiology* ; Overweight/epidemiology* ; Pregnancy ; Pregnancy Complications ; Pregnant Women ; Risk Factors ; Thinness/epidemiology* ; Weight Gain