Functions of the analysis inhabitants
The entire functions of overall research population, men users and females professionals are given within the dining table 1. Throughout the complete population, the suggest birth weight is step 3.step three kg, and you will was quite large when you look at the men in contrast to women (3.3 and you can step 3.dos kg, respectively). The brand new prevalence to be overweight and you can over weight are highest inside males than in women (overweight: fourteen.0%, ten.6% respectively; obesity: fourteen.7%, 11.3% respectively). The brand new imply opinions (SD) out of FMI from inside the teens was 5.8 (±dos.5) kg/m dos on complete population, 5.0 (±2.5) kg/m 2 from inside the men and you can 6.eight (±dos.2) kg/meters 2 in women. The newest suggest opinions (SD) away from LMI was 15.0 (±dos.1) kg/m 2 on full people, 16.0 (±2.0) kg/meters dos during the people and you can thirteen.8 (±1.5) kg/yards dos in females.
Table 2 describes characteristics of three groups: those with complete data (n=884), those with missing values on birth weight or BMI (n=206) and those with missing values on DXA (n=420). There were no significant differences in the distribution of characteristics, including birth weight, BMI, FMI and LMI among the three groups. However, instanthookups those without birth weight or BMI data had higher percentage of those living in the capital area, and being in the lowest tertile of household income compared with those with complete data. Furthermore, both of the distribution of area of residence and household income differed significantly from the complete case (P<0.01 for both area of residence and household income).
BMI of adolescents tended to increase linearly with increasing birth weight in total participants, men and women (P for trend: <0.01, 0.01 and 0.05, respectively) as presented in figure 2. Table 3 shows the total and sex-stratified ORs of being overweight and being obese according to birth weight. In the total population, the unadjusted OR for overweight in the high birth weight group (highest 25th percentile group) was 1.87 (95% CI 1.17 to 2.97) compared with the reference group. In the adjusted analysis, the high birth weight group also had higher risk of being overweight (aOR 1.75, 95% CI 1.11 to 2.76) compared with the reference group. In men, the unadjusted OR for being overweight was 2.32 (95% CI 1.30 to 4.16), and the association remained significant after adjustment of covariates (aOR 2.19, 95% CI 1.20 to 3.98). However, there was no association between high birth weight and obesity in men (aOR 1.16, 95% CI 0.62 to 2.18). In contrast, in women, adjusted analysis demonstrated the association between high birth weight and being obese after adjustment (aOR 2.13, 95% CI 1.03 to 4.41), but no association with being overweight (aOR 1.05, 95% CI 0.47 to 2.37). After data imputation, results that were significant in the complete case analysis remained consistent. In the total population and male population, the high birth weight group had higher risk of being overweight (aOR 1.70, 95% CI 1.08 to 2.54; aOR 2.12, 95% CI 1.17 to 3.99) compared with the reference group after adjustment. In female population, high birth weight group had higher risk of being obese (aOR 2.18, 95% CI 1.11 to 4.49) compared with the reference group after adjustment.
Minimum squares technique of body mass index in total participants (n=1304), male (n=693) and you can girls (n=611). We modified to own decades, sex, household and you may house earnings considering birth pounds.
Matchmaking between delivery pounds and the entire body structure
The associations between birth weight, fat mass and lean mass are presented in figure 3 (total participants), figure 4 (men) and figure 5 (women). After adjusting for sociodemographic factors, the adjusted mean values of FMI increased significantly with increasing birth weight in the total population (P for trend: 0.03). However, LMI showed no significant increase with increasing birth weight (P for trend: 0.08). In male participants, higher birth weight was neither associated with higher FMI nor LMI (P for trend: 0.20, 0.25, respectively). In female participants, higher birth weight was associated with higher FMI (P for trend: 0.03), while LMI showed an inverse U-shape (P for trend: 0.25). Even after imputing the missing data, the overall trend of positive correlation between birth weight and FMI did not change. In women and the total population, FMI increased significantly with increasing birth weight (P for trend: <0.01 for both women and the total population). However, LMI did not increase with increasing birth weight (P for trend: 0.20).