| Literature DB >> 25388405 |
D-K Li1, J R Ferber2, R Odouli2.
Abstract
BACKGROUND/Entities:
Mesh:
Substances:
Year: 2014 PMID: 25388405 PMCID: PMC4389720 DOI: 10.1038/ijo.2014.196
Source DB: PubMed Journal: Int J Obes (Lond) ISSN: 0307-0565 Impact factor: 5.095
Characteristics of the study population by maternal caffeine intake
| ⩾ | |||||
|---|---|---|---|---|---|
| Age at delivery | <25 | 19 (15.3) | 59 (15.8) | 10 (8.5) | |
| 25–30 | 44 (35.5) | 108 (29.0) | 26 (22.0) | ||
| 30–35 | 40 (32.3) | 129 (34.6) | 46 (39.0) | ||
| 35+ | 21 (16.9) | 77 (20.6) | 36 (30.5) | 0.03 | |
| Education | <College | 76 (61.8) | 210 (56.3) | 63 (53.4) | |
| College degree | 32 (26.0) | 108 (29.0) | 36 (30.5) | ||
| Graduate school | 15 (12.2) | 55 (14.8) | 19 (16.1) | 0.75 | |
| Race | White | 28 (22.6) | 129 (34.6) | 55 (46.6) | |
| Black | 10 (8.1) | 24 (6.4) | 4 (3.4) | ||
| Hispanic | 35 (28.2) | 94 (25.2) | 16 (13.6) | ||
| Asian/Pacific Islander | 47 (37.9) | 108 (29.0) | 35 (29.7) | ||
| Other/unknown | 4 (3.2) | 18 (4.8) | 8 (6.8) | 0.003 | |
| Income | <$30 000 | 27 (22.9) | 68 (19.1) | 18 (16.2) | |
| $30 000–60 000 | 45 (38.1) | 152 (42.7) | 46 (41.4) | ||
| ⩾$60 000 | 46 (39.0) | 136 (38.2) | 47 (42.3) | 0.71 | |
| Marital status | Single | 7 (5.7) | 21 (5.6) | 4 (3.4) | |
| Married | 106 (86.2) | 302 (81.0) | 96 (81.4) | ||
| Live with partner | 9 (7.3) | 42 (11.3) | 13 (11.0) | ||
| Other | 1 (0.8) | 8 (2.1) | 5 (4.2) | 0.44 | |
| Prepregnancy BMI | <25 | 90 (72.6) | 245 (65.7) | 83 (70.3) | |
| ⩾25 | 34 (27.4) | 128 (34.3) | 35 (29.7) | 0.30 | |
| Preexisting or gestational diabetes | No | 113 (95.0) | 332 (93.0) | 100 (88.5) | |
| Yes | 6 (5.0) | 25 (7.0) | 13 (11.5) | 0.15 | |
| Number of previous live births | 0 | 59 (47.6) | 157 (42.1) | 48 (40.7) | |
| 1 | 46 (37.1) | 145 (38.9) | 45 (38.1) | ||
| 2+ | 19 (15.3) | 71 (19.0) | 25 (21.2) | 0.72 | |
| Maternal smoking during pregnancy | No | 123 (99.2) | 339 (90.9) | 92 (78.0) | |
| Yes | 1 (0.8) | 34 (9.1) | 26 (22.0) | <0.001 | |
| Preterm delivery | No | 113 (91.9) | 346 (93.5) | 111 (94.9) | |
| Yes | 10 (8.1) | 24 (6.5) | 6 (5.1) | 0.64 | |
| Small-for-gestational-age | No | 108 (88.5) | 338 (91.6) | 107 (92.2) | |
| Yes | 14 (11.5) | 31 (8.4) | 9 (7.8) | 0.52 | |
| Child sex | Male | 61 (49.2) | 188 (50.4) | 61 (51.7) | |
| Female | 63 (50.8) | 185 (49.6) | 57 (48.3) | 0.93 | |
| Breastfed | No | 9 (7.3) | 21 (5.7) | 16 (13.6) | |
| Yes | 114 (92.7) | 351 (94.4) | 102 (86.4) | 0.02 | |
| Eat at least 5 servings of fruits and vegetables per day | No | 24 (24.0) | 85 (30.4) | 22 (25.0) | |
| Yes | 76 (76.0) | 195 (69.6) | 66 (75.0) | 0.38 | |
| TV, computer, video game time limited to 1h per day | No | 15 (16.9) | 56 (21.1) | 21 (25.9) | |
| Yes | 74 (83.2) | 210 (79.0) | 60 (74.1) | 0.35 | |
| Exercise at least 30 min per day | No | 8 (9.1) | 25 (9.4) | 9 (11.1) | |
| Yes | 80 (90.9) | 242 (90.6) | 72 (88.9) | 0.88 | |
| Play any sports | No | 10 (13.3) | 40 (19.4) | 11 (17.2) | |
| Yes | 65 (86.7) | 166 (80.6) | 53 (82.8) | 0.49 | |
| Number of BMI measurements | 9.4±6.8 | 9.6±12.1 | 8.5±6.0 | 0.60 | |
| Age at most recent BMI measurement (mean±s.d.) | 12.7±3.6 | 11.9±4.1 | 11.8±4.2 | 0.11 | |
Abbreviations: ANOVA, analysis of variance; BMI, body mass index.
Childhood characteristics from a subsample of children whose data was collected during clinical visits including well-child visits.
Measurements above age 2 only.
P-value from ANOVA F-test.
In-utero exposure to caffeine and the risk of obesitya in offspring
| N | |||
|---|---|---|---|
| No | 124 | Reference | |
| Yes | 491 | 1.87 | 1.12–3.12 |
| Categorical | |||
| <150 mg per day | 373 | 1.77 | 1.05–3.00 |
| ⩾150 mg per day | 118 | 2.37 | 1.24–4.52 |
| Linear | |||
| Caffeine mg per day | 615 | 1.23 | 0.99–1.53 |
Abbreviations: aOR, adjusted odds ratio; BMI, body mass index; CI, confidence interval; GEE, generalized estimating equation.
Obesity defined as ⩾95 percentile of age- and gender-specific BMI based on the Centers for Disease Control and Prevention criteria.[52]
OR from GEE model with repeated measurements, adjusted for child's exact age at each measurement, child gender, maternal age at delivery, smoking during pregnancy, prepregnancy BMI and race. Further adjustment for following factors did not change the results: maternal education level, marital status, parity, preexisting or gestational diabetes, income, preterm delivery, small-for-gestational-age or birthweight, breastfeeding, and childhood characteristics such as fruit and vegetable intake, TV watching and exercise.
Caffeine intake (mg per day) was log10 transformed because of skewed distribution.
Relationship between in-utero exposure to caffeine and obesitya in offspring, by source of caffeine
| N | |||
|---|---|---|---|
| None | 124 | Reference | |
| Coffee only | 85 | 2.26 | 1.12–4.58 |
| Tea only | 34 | 1.43 | 0.61–3.36 |
| Soda only | 107 | 1.93 | 1.02–3.65 |
| Other/multiple sources | 265 | 1.79 | 1.03–3.12 |
Abbreviations: aOR, adjusted odds ratio; BMI, body mass index; CI, confidence interval; GEE, generalized estimating equation.
Obesity defined as ⩾95 percentile of age- and gender-specific BMI based on the Centers for Disease Control and Prevention criteria.[52]
OR from GEE model with repeated measurements, adjusted for child's exact age at each measurement, child gender, maternal age at delivery, smoking during pregnancy, prepregnancy BMI and race. Further adjustment for following factors did not change the results: maternal education level, marital status, parity, preexisting or gestational diabetes, income, preterm delivery, small-for-gestational-age or birthweight, breastfeeding, and childhood characteristics such as fruit and vegetable intake, TV watching and exercise.
In-utero exposure to caffeine and the risk of obesitya in offspring among children with at least 11 years of follow-up
| No caffeine | 79 (88.8) | 10 (11.2) | Reference | |
| <150 | 181 (83.0) | 37 (17.0) | 1.44 | 0.65–3.18 |
| ⩾150 | 53 (72.6) | 20 (27.4) | 3.21 | 1.27–8.07 |
| No caffeine | 79 (85.9) | 13 (14.1) | Reference | |
| <150 | 181 (75.4) | 59 (24.6) | 1.93 | 0.98–3.79 |
| ⩾150 | 53 (77.9) | 15 (22.1) | 1.97 | 0.83–4.67 |
Abbreviations: aOR, adjusted odds ratio; BMI, body mass index; CI, confidence interval.
Obesity defined as ⩾95th percentile of age- and gender-specific BMI based on the Centers for Disease Control and Prevention criteria.[52]
From logistic regression model, adjusted for child gender, maternal age at delivery, prepregnancy BMI, smoking during pregnancy and race. Further adjustment for following factors did not change the results: maternal education level, marital status, parity, preexisting or gestational diabetes, income, preterm delivery, small-for-gestational-age or birthweight, breastfeeding, and childhood characteristics such as fruit and vegetable intake, TV watching and exercise.
⩾50% of measurements met the definition of obesity and the child remained obese at the end of follow-up (vs never obese).
<50% of measurements met the definition of obesity or the child was no longer obese at the end of follow-up (vs never obese).
In-utero exposure to caffeine and the risk of obesitya in offspring, by gender
| N | |||
|---|---|---|---|
| No caffeine | 63 | Reference | |
| <150 | 185 | 1.24 | (0.61–2.50) |
| ⩾150 | 57 | 3.32 | (1.49–7.41) |
| No caffeine | 61 | Reference | |
| <150 | 188 | 2.48 | (1.19–5.17) |
| ⩾150 | 61 | 1.53 | (0.60–3.92) |
Abbreviations: aOR, adjusted odds ratio; BMI, body mass index; CI, confidence interval; GEE, generalized estimating equation.
Obesity defined as ⩾95 percentile of age- and gender-specific BMI based on the Centers for Disease Control and Prevention criteria.[52]
OR from GEE model with repeated measurements, adjusted for child's exact age at each measurement, maternal age at delivery, prepregnancy BMI, smoking during pregnancy and race. Further adjustment for following factors did not change the results: maternal education level, marital status, parity, preexisting or gestational diabetes, income, preterm delivery, small-for-gestational-age or birthweight, breastfeeding, and childhood characteristics such as fruit and vegetable intake, TV watching and exercise.