Abstract
Studies investigating the relationship between maternal passive smoking and the risk of preterm birth have reached inconsistent conclusions. A birth cohort study that included 10,095 nonsmoking women who delivered a singleton live birth was carried out in Lanzhou, China, between 2010 and 2012. Exposure to passive smoking during pregnancy was associated with an increased risk of very preterm birth (<32 completed weeks of gestation; odds ratio = 1.98, 95% confidence interval: 1.41, 2.76) but not moderate preterm birth (32–36 completed weeks of gestation; odds ratio = 0.98, 95% confidence interval: 0.81, 1.19). Risk of very preterm birth increased with the duration of exposure (P for trend = 0.0014). There was no variability in exposures by trimester. The associations were consistent for both medically indicated and spontaneous preterm births. Overall, our findings support a positive association between passive smoking and the risk of very preterm birth.
Keywords: birth cohort, China, passive smoking, preterm birth
Preterm birth is the leading cause of neonatal deaths and is associated with various infant morbidities, such as acute respiratory illness, gastrointestinal and immunologic deficits, lifelong neurologic handicaps, and chronic diseases, that can extend into adulthood (1–3). In addition to the intense physical and emotional tolls associated with these illnesses, economic costs to families and society due to neonatal intensive care, ongoing health care, and specialized educational needs can be devastating.
The estimated prevalence of preterm birth ranges from 5% to 18% worldwide, with the lowest rates occurring in more developed areas and the highest rates in less developed areas (4). During the past decade, a rising trend of preterm births has been observed in most countries for which reliable data were available (4). Finding a solution to this growing problem is a priority for Millennium Development Goal 4 by the World Health Organization (5), as preterm birth continues to emerge as a major public health concern.
Several factors are believed to predispose women to preterm delivery, including underlying infection, certain preexisting anatomical considerations, and active smoking during pregnancy. Unlike disease processes, tobacco smoke is an environmental exposure that is much easier to eliminate. Though maternal active smoking is a well-documented risk factor for preterm delivery (6), evidence for passive smoking has been mixed (7). Some studies suggested that maternal passive smoking was associated with an increased risk of preterm birth (8–14), whereas others found no association (15–21). A systematic review and meta-analysis showed no significant association between passive smoking and preterm birth (22), although the ranges of gestational ages in the different populations varied between these studies, complicating the comparability of the results. Decreasing gestational age at birth is associated with increasing rates of mortality and morbidity (4), and thus the relationship between passive smoking and the risk of preterm birth may vary with gestational age. In addition, preterm birth is a complex outcome that can be further categorized into medically indicated or spontaneous preterm birth based on cause. To our knowledge, our study is the first to comprehensively examine the association between passive smoking and preterm birth by clinical subtypes.
China contains one fifth of the world's population and has the second highest number of preterm births in the world (23). According to results from a national survey in China, very few women (3.2%) and a large number of men (48.9%) are active smokers (24). This fact provides a unique opportunity for us to study passive smoking and reproductive health in nonsmoking women. Given the previous inconclusive findings regarding maternal passive smoking and preterm birth risk, we conducted a large birth cohort study in Lanzhou, China, to examine the relationship by various clinical subtypes.
METHODS
A study of a birth cohort was conducted in 2010–2012 at the Gansu Provincial Maternity and Child Care Hospital, the largest maternity and child care hospital in Lanzhou, China. Pregnant women who came to the hospital for delivery at 20 weeks of gestation or more, who had no mental illness, and who were 18 years of age or older were eligible. A total of 14,535 pregnant women came to the hospital for delivery, of whom 176 were judged to be ineligible for the study (13 had mental illness, 39 were younger than 18 years of age, and 124 gave birth at less than 20 gestational weeks). Thus, a total of 14,359 eligible women were approached for participation. Of those, 3,712 refused to participate and 105 did not complete in-person interviews, which yielded 10,542 (73.4%) women who completed in-person interviews, 10,179 of whom had a singleton live birth.
All study procedures were approved by the human investigation committees at the Gansu Provincial Maternity and Child Care Hospital and Yale University. Eligible women were informed of study procedure upon their arrival at the hospital for delivery. After obtaining written consent, trained study interviewers conducted in-person interviews at the hospital using a standardized and structured questionnaire. The majority of women (84%) were interviewed within 1 to 3 days after delivery. The questionnaire collected information regarding demographic factors, reproductive and medical history, smoking behavior, alcohol and tea consumption, occupational and residential history, physical activity level, and diet. Information on birth outcomes and pregnancy complications were abstracted from the medical records.
Active smokers were defined as women who smoked 1 or more cigarettes per day for at least 1 month. Because so few women were active smokers (n = 85), we excluded active smokers from the study population, which yielded a final sample size of 10,094. Passive smokers were defined as women who were exposed to cigarette smoke at home, at work, during social and recreational activities, and/or while commuting to and from work for at least 30 minutes per week during pregnancy. Information on passive smoking exposure, duration (hours per day) of exposure, and location (home vs. other location) was collected separately for each trimester.
Preterm birth was defined as delivery before 37 completed weeks of gestation. The gestational age at delivery was calculated in completed weeks from the first day of the last menstrual period. According to the World Health Organization classification (5), preterm birth was divided into moderate preterm birth (32–36 weeks of gestation), very preterm birth (28–31 weeks of gestation), and extremely preterm birth (<28 completed weeks of gestation). To increase statistical power, we combined very preterm and extremely preterm births into a single group labeled very preterm birth. Preterm births were further classified as either medically indicated or spontaneous (25, 26). A medically indicated preterm birth occurs when a placental, uterine, fetal, or maternal condition exists that prompts the medical team to proceed with delivery after the risks and benefits of continuing pregnancy are weighed against the risks and benefits of early delivery. Examples include placenta or vasa previa, placenta accreta, placental abruption, prior classical cesarean delivery, uterine rupture or dehiscence, fetal growth restriction, select fetal anomalies, severe preeclampsia, uncontrolled gestational or chronic hypertension, complicated pregestational diabetes, and oligohydramnios. Medically indicated preterm birth does not include deliveries that result from spontaneous preterm labor or preterm premature rupture of membranes (PPROM).
Univariate analyses were used to compare selected characteristics between preterm and term births. P values were obtained using χ2 test or Fisher's exact test for categorical variables and Student's t test for continuous variables. Unconditional logistic regression models were used to estimate odds ratios and 95% confidence intervals for the association of passive smoking with preterm birth and its clinical subtypes. In the final models, we adjusted for potential confounding variables, including maternal age (<25, 25–29, ≥30 years), years of education (<10, 10–15, >15), employment status during pregnancy (yes or no), preeclampsia/eclampsia (yes or no), gestational diabetes (yes or no), parity (nulliparous or parous), history of preterm birth (yes or no), and cesarean delivery of the current birth (yes or no). Additional adjustment for alcohol consumption, maternal prepregnancy body mass index (weight (kg)/height (m)2), maternal weight gain, physical activity during pregnancy, and infant sex did not result in material changes in the observed associations and thus were not included in the final models. All analyses were performed using SAS software, version 9.2 (SAS Institute, Inc., Cary, North Carolina).
RESULTS
Of the 10,094 singleton live births, 10.0% were preterm with a gestational age less than 37 completed weeks. Of those 1,009 preterm births, 81.6% (n = 823) were moderate preterm births (32–36 weeks of gestation) and 18.4% (n = 186) were very preterm births (<32 weeks of gestation). One third of the preterm births were medically indicated (n = 337), with a mean gestational age of 33.6 (standard deviation, 2.5) weeks. Spontaneous preterm births accounted for approximately two thirds of the preterm births (n = 672), with a mean gestational age of 33.5 (standard deviation, 3.2) weeks.
Table 1 shows the distributions of selected characteristics in women with preterm and term deliveries. Women who had preterm deliveries were more likely to be either younger than 25 years of age or older than 30 years of age, have fewer years of education, be unemployed during pregnancy, have a higher prepregnancy body mass index, be parous, and have a history of preterm delivery. Women who were diagnosed with preeclampsia or diabetes were also more likely to have a preterm birth. Distributions of alcohol consumption and infant sex were similar for preterm and term deliveries.
Table 1.
Distribution of Selected Characteristics of the Study Population (n = 10,094), Urban China, 2010–2012
| Characteristic | Preterm Birth (n = 1,009) |
Full-Term Birth (n = 9,085) |
P Valuea | ||
|---|---|---|---|---|---|
| No. | % | No. | % | ||
| Age, years | <0.0001 | ||||
| <25 | 239 | 23.7 | 1,383 | 15.2 | |
| 25–29 | 361 | 35.8 | 4,452 | 49.0 | |
| ≥30 | 409 | 40.5 | 3,250 | 35.8 | |
| Education, years | <0.0001 | ||||
| ≤9 | 392 | 39.7 | 1,835 | 20.6 | |
| 10–15 | 373 | 37.8 | 3,556 | 39.8 | |
| ≥16 | 222 | 22.5 | 3,532 | 39.6 | |
| Missing | 22 | 162 | |||
| Employment status | <0.0001 | ||||
| No | 593 | 58.8 | 4,287 | 47.2 | |
| Yes | 416 | 41.2 | 4,798 | 52.8 | |
| Parity | <0.0001 | ||||
| Nulliparous | 623 | 61.7 | 6,751 | 74.3 | |
| Parous | 386 | 38.3 | 2,334 | 25.7 | |
| History of preterm delivery | <0.0001 | ||||
| No | 962 | 95.3 | 9,053 | 99.6 | |
| Yes | 47 | 4.7 | 32 | 0.4 | |
| Preeclampsia | <0.0001 | ||||
| No | 876 | 86.8 | 8,887 | 97.8 | |
| Yes | 133 | 13.2 | 198 | 2.2 | |
| Diabetes | 0.024 | ||||
| Yes | 992 | 98.3 | 9,000 | 99.1 | |
| No | 17 | 1.7 | 85 | 0.9 | |
| Prepregnancy body mass indexb | 0.025 | ||||
| ≤18.5 | 192 | 20.2 | 1,863 | 21.2 | |
| 18.6–23.9 | 629 | 66.2 | 5,996 | 68.1 | |
| ≥24 | 129 | 13.6 | 941 | 10.7 | |
| Missing | 59 | 285 | |||
| Alcohol drinking during pregnancy | 0.81 | ||||
| No | 1,007 | 99.8 | 9,070 | 99.8 | |
| Yes | 2 | 0.2 | 15 | 0.2 | |
| Cesarean delivery | <0.0001 | ||||
| No | 482 | 49.8 | 5,680 | 63.0 | |
| Yes | 486 | 50.2 | 3,334 | 37.0 | |
| Missing | 41 | 71 | |||
| Sex of the child | 0.15 | ||||
| Boy | 551 | 54.9 | 4,761 | 52.6 | |
| Girl | 452 | 45.1 | 4,297 | 47.4 | |
| Missing | 6 | 27 | |||
a The analysis did not account for missing data.
b Weight (kg)/height (m)2.
As shown in Table 2, passive smoking during pregnancy was slightly associated with an increased risk of preterm birth overall (odds ratio (OR) = 1.12, 95% confidence interval (CI): 0.95, 1.32). After stratification by gestational age, a 98% increased risk was observed for very preterm birth (OR = 1.98, 95% CI: 1.41, 2.76) but not moderate preterm birth. The risk of a very preterm birth increased with the duration of exposure (P for trend = 0.0014). When the association was examined by exposure location, a significantly increased risk of very preterm birth was associated with exposure to passive smoking at home (OR = 2.12, 95% CI: 1.48, 3.03) but not at work (OR = 1.58, 95% CI: 0.90, 2.79). Risk increased with increasing duration of exposure at home (P < 0.0001) and at other locations (P = 0.032; data not shown). Similar results were seen when using mutually exclusive categories for location of exposure (data not shown). These observations showed similar patterns across exposure during all pregnancy trimesters.
Table 2.
Associations Between Passive Smoking and Preterm Birth (n = 10,094), Urban China, 2010–2012
| Passive Smoking | No. of Term Births | Preterm Births (<37 Weeks of Gestation) |
Moderate Preterm Births (32–36 Weeks of Gestation) |
Very Preterm Births (<32 Weeks of Gestation) |
||||||
|---|---|---|---|---|---|---|---|---|---|---|
| No. | ORa | 95% CI | No. | ORa | 95% CI | No. | ORa | 95% CI | ||
| No | 7,405 | 783 | 1.00 | Referent | 657 | 1.00 | Referent | 126 | 1.00 | Referent |
| During the entire pregnancy | ||||||||||
| Yes | 1,680 | 226 | 1.12 | 0.95, 1.32 | 166 | 0.98 | 0.81, 1.19 | 60 | 1.98 | 1.41, 2.76 |
| Durationb, hours/day | ||||||||||
| <1 | 994 | 135 | 1.10 | 0.90, 1.36 | 100 | 0.98 | 0.78, 1.23 | 35 | 1.89 | 1.26, 2.84 |
| ≥1 | 458 | 67 | 1.27 | 0.96, 1.69 | 47 | 1.05 | 0.76, 1.46 | 20 | 2.61 | 1.56, 4.34 |
| P for trend | 0.19 | 0.67 | 0.0014 | |||||||
| Exposure location | ||||||||||
| Home | 1,243 | 189 | 1.17 | 0.98, 1.41 | 137 | 1.02 | 0.83, 1.25 | 52 | 2.12 | 1.48, 3.03 |
| Other | 695 | 63 | 0.92 | 0.70, 1.22 | 48 | 0.82 | 0.60, 1.12 | 15 | 1.58 | 0.90, 2.77 |
| During the first trimester | ||||||||||
| Yes | 1,574 | 212 | 1.11 | 0.94, 1.32 | 156 | 0.98 | 0.81, 1.18 | 56 | 1.98 | 1.41, 2.79 |
| Duration, hours/day | ||||||||||
| <1 | 822 | 115 | 1.09 | 0.88, 1.37 | 83 | 0.95 | 0.74, 1.22 | 32 | 2.00 | 1.30, 3.06 |
| ≥1 | 532 | 74 | 1.24 | 0.95, 1.62 | 53 | 1.04 | 0.76, 1.42 | 21 | 2.46 | 1.50, 4.03 |
| P for trend | 0.25 | 0.68 | 0.0023 | |||||||
| Exposure location | ||||||||||
| Home | 1,155 | 176 | 1.16 | 0.96, 1.40 | 126 | 0.99 | 0.80, 1.22 | 50 | 2.22 | 1.55, 3.19 |
| Other | 610 | 54 | 0.91 | 0.68, 1.23 | 40 | 0.79 | 0.56, 1.12 | 14 | 1.66 | 0.93, 2.96 |
| During the second trimester | ||||||||||
| Yes | 1,437 | 192 | 1.10 | 0.92, 1.31 | 139 | 0.94 | 0.77, 1.15 | 53 | 2.09 | 1.47, 2.96 |
| Duration, hours/day | ||||||||||
| <1 | 775 | 110 | 1.11 | 0.88, 1.39 | 80 | 0.96 | 0.74, 1.24 | 30 | 2.03 | 1.31, 3.14 |
| ≥1 | 492 | 69 | 1.22 | 0.92, 1.61 | 48 | 1.00 | 0.72, 1.38 | 21 | 2.55 | 1.55, 4.20 |
| P for trend | 0.15 | 0.73 | 0.0005 | |||||||
| Exposure location | ||||||||||
| Home | 1,050 | 163 | 1.18 | 0.97, 1.43 | 118 | 1.01 | 0.81, 1.26 | 45 | 2.20 | 1.51, 3.20 |
| Other | 543 | 44 | 0.81 | 0.58, 1.13 | 33 | 0.70 | 0.48, 1.02 | 11 | 1.56 | 0.82, 2.94 |
| During the third trimester | ||||||||||
| Yes | 1,271 | 177 | 1.13 | 0.94, 1.37 | 129 | 0.98 | 0.79, 1.21 | 48 | 2.06 | 1.43, 2.97 |
| Duration, hours/day | ||||||||||
| <1 | 716 | 103 | 1.12 | 0.88, 1.41 | 73 | 0.95 | 0.73, 1.24 | 30 | 2.08 | 1.34, 3.23 |
| ≥1 | 421 | 63 | 1.31 | 0.98, 1.75 | 47 | 1.13 | 0.81, 1.57 | 16 | 2.39 | 1.38, 4.16 |
| P for trend | 0.26 | 0.69 | 0.0029 | |||||||
| Exposure location | ||||||||||
| Home | 948 | 153 | 1.22 | 1.00, 1.49 | 112 | 1.06 | 0.85, 1.32 | 41 | 2.14 | 1.45, 3.15 |
| Other | 452 | 39 | 0.88 | 0.62, 1.25 | 29 | 0.75 | 0.50, 1.12 | 10 | 1.69 | 0.86, 3.31 |
Abbreviations: CI, confidence interval; OR, odds ratio.
a Adjusted for maternal age, educational level, employment status, preeclampsia, diabetes, parity, history of preterm delivery, and cesarian delivery.
b We did not have this information for a total of 24 preterm births and 228 term births.
We then analyzed the data separately for medically indicated and spontaneous preterm births (Tables 3 and 4). The associations with passive smoking were similar for both. Significant associations were observed for medically indicated and spontaneous very preterm births but not for medically indicated or spontaneous moderate preterm births.
Table 3.
Associations Between Passive Smoking and Preterm Birth by Clinical Subtype (n = 10,094), Urban China, 2010–2012
| Passive Smoking | No. of Term Births | Subtype of Preterm Birth |
|||||
|---|---|---|---|---|---|---|---|
| Medically Indicated (n = 337) |
Spontaneous (n = 672) |
||||||
| No. | ORa | 95% CI | No. | ORa | 95% CI | ||
| No | 7,405 | 252 | 1.00 | Referent | 531 | 1.00 | Referent |
| During the entire pregnancy | |||||||
| Yes | 1,680 | 85 | 1.23 | 0.94, 1.61 | 141 | 1.07 | 0.88, 1.31 |
| Duration, hours/day | |||||||
| <1 | 994 | 51 | 1.18 | 0.85, 1.64 | 84 | 1.08 | 0.85, 1.39 |
| ≥1 | 458 | 26 | 1.54 | 0.98, 2.41 | 41 | 1.15 | 0.82, 1.62 |
| P for trend | 0.30 | 0.33 | |||||
| Exposure location | |||||||
| Home | 1243 | 73 | 1.30 | 0.98, 1.74 | 116 | 1.12 | 0.90, 1.40 |
| Other | 695 | 22 | 0.96 | 0.60, 1.53 | 41 | 0.89 | 0.64, 1.24 |
| During the first trimester | |||||||
| Yes | 1,574 | 81 | 1.22 | 0.93, 1.61 | 131 | 1.06 | 0.87, 1.31 |
| Duration, hours/day | |||||||
| <1 | 822 | 45 | 1.21 | 0.85, 1.71 | 70 | 1.06 | 0.81, 1.38 |
| ≥1 | 532 | 29 | 1.44 | 0.94, 2.20 | 45 | 1.15 | 0.83, 1.58 |
| P for trend | 0.33 | 0.45 | |||||
| Exposure location | |||||||
| Home | 1,155 | 69 | 1.30 | 0.97, 1.74 | 107 | 1.11 | 0.89, 1.39 |
| Other | 610 | 19 | 0.97 | 0.59, 1.61 | 35 | 0.87 | 0.61, 1.25 |
| During the second trimester | |||||||
| Yes | 1,437 | 71 | 1.18 | 0.88, 1.57 | 121 | 1.08 | 0.87, 1.33 |
| Duration, hours/day | |||||||
| <1 | 775 | 41 | 1.12 | 0.78, 1.61 | 69 | 1.12 | 0.86, 1.47 |
| ≥1 | 492 | 26 | 1.45 | 0.93, 2.27 | 43 | 1.13 | 0.81, 1.57 |
| P for trend | 0.49 | 0.28 | |||||
| Exposure location | |||||||
| Home | 1,050 | 63 | 1.27 | 0.94, 1.73 | 100 | 1.15 | 0.91, 1.45 |
| Other | 543 | 14 | 0.79 | 0.44, 1.40 | 30 | 0.83 | 0.56, 1.22 |
| During the third trimester | |||||||
| Yes | 1,271 | 64 | 1.20 | 0.89, 1.62 | 113 | 1.13 | 0.91, 1.41 |
| Duration, hours/day | |||||||
| <1 | 716 | 36 | 1.08 | 0.74, 1.58 | 67 | 1.16 | 0.88, 1.52 |
| ≥1 | 421 | 24 | 1.56 | 0.98, 2.48 | 39 | 1.21 | 0.85, 1.71 |
| P for trend | 0.38 | 0.40 | |||||
| Exposure location | |||||||
| Home | 948 | 58 | 1.31 | 0.96, 1.80 | 95 | 1.21 | 0.95, 1.53 |
| Other | 452 | 12 | 0.85 | 0.45, 1.58 | 27 | 0.89 | 0.59, 1.34 |
Abbreviations: CI, confidence interval; OR, odds ratio.
a Adjusted for maternal age, educational level, employment status, parity, history of preterm delivery, and cesarian delivery.
Table 4.
Associations Between Passive Smoking and Very Preterm Birtha by Clinical Subtype (n = 10,094), Urban China, 2010–2012
| Passive Smoking | Subtype of Preterm Birth |
|||||
|---|---|---|---|---|---|---|
| Medically Indicated (n = 337) |
Spontaneous (n = 128) |
|||||
| No. | ORb | 95% CI | No. | ORb | 95% CI | |
| No | 38 | 1.00 | Referent | 88 | 1.00 | Referent |
| During the entire pregnancy | ||||||
| Yes | 20 | 2.09 | 1.18, 3.69 | 40 | 1.98 | 1.33, 2.97 |
| Duration, hours/day | ||||||
| <1 | 11 | 1.83 | 0.90, 3.73 | 24 | 2.06 | 1.27, 3.33 |
| ≥1 | 8 | 3.57 | 1.60, 8.00 | 12 | 2.14 | 1.12, 4.11 |
| P for trend | 0.044 | 0.010 | ||||
| Exposure location | ||||||
| Home | 17 | 2.11 | 1.15, 3.87 | 35 | 2.22 | 1.45, 3.41 |
| Other | 4 | 1.40 | 0.49, 4.03 | 11 | 1.64 | 0.85, 3.17 |
| During the first trimester | ||||||
| Yes | 19 | 2.11 | 1.18, 3.78 | 37 | 1.97 | 1.30, 2.98 |
| Duration, hours/day | ||||||
| <1 | 10 | 1.91 | 0.91, 4.00 | 22 | 2.22 | 1.34, 3.67 |
| ≥1 | 9 | 3.53 | 1.64, 7.61 | 12 | 1.98 | 1.05, 3.75 |
| P for trend | 0.060 | 0.015 | ||||
| Exposure location | ||||||
| Home | 16 | 2.16 | 1.16, 4.01 | 34 | 2.35 | 1.52, 3.62 |
| Other | 4 | 1.66 | 0.58, 4.77 | 10 | 1.66 | 0.84, 3.30 |
| During the second trimester | ||||||
| Yes | 18 | 2.19 | 1.21, 3.97 | 35 | 2.14 | 1.40, 3.26 |
| Duration, hours/day | ||||||
| <1 | 10 | 1.96 | 0.93, 4.10 | 20 | 2.28 | 1.36, 3.83 |
| ≥1 | 8 | 3.33 | 1.49, 7.44 | 13 | 2.17 | 1.16, 4.08 |
| P for trend | 0.029 | 0.0059 | ||||
| Exposure location | ||||||
| Home | 15 | 2.16 | 1.14, 4.07 | 30 | 2.34 | 1.49, 3.68 |
| Other | 3 | 1.33 | 0.40, 4.42 | 8 | 1.69 | 0.80, 3.56 |
| During the third trimester | ||||||
| Yes | 16 | 2.16 | 1.16, 4.00 | 32 | 2.16 | 1.40, 3.35 |
| Duration, hours/day | ||||||
| <1 | 9 | 1.87 | 0.87, 4.04 | 21 | 2.38 | 1.42, 4.00 |
| ≥1 | 6 | 2.94 | 1.19, 7.24 | 10 | 2.14 | 1.08, 4.26 |
| P for trend | 0.11 | 0.013 | ||||
| Exposure location | ||||||
| Home | 14 | 2.18 | 1.14, 4.19 | 27 | 2.31 | 1.45, 3.70 |
| Other | 2 | 1.15 | 0.27, 4.90 | 8 | 1.92 | 0.90, 4.08 |
Abbreviations: CI, confidence interval; OR, odds ratio.
a Less than 32 weeks of gestation.
b Adjusted for maternal age, educational level, employment status, parity, history of preterm delivery, and cesarian delivery.
We further stratified the analysis for spontaneous very preterm births by the presence or absence of PPROM (Table 5). The significant associations between passive smoking and spontaneous very preterm birth were seen for women without PPROM (OR = 2.72, 95% CI: 1.70, 4.34) but not for those with PPROM (OR = 0.91, 95% CI: 0.39, 2.13).
Table 5.
Associations Between Passive Smoking and Spontaneous Very Preterm Birtha by PPROM Status (n = 10,094), Urban China, 2010–2012
| Passive Smoking | No. of Term Births | Very Preterm Births |
|||||
|---|---|---|---|---|---|---|---|
| With PPROM (n = 34) |
Without PPROM (n = 94) |
||||||
| No. | ORb | 95% CI | No. | ORb | 95% CI | ||
| No | 7,406 | 27 | 1.00 | Referent | 61 | 1.00 | Referent |
| During the entire pregnancy | |||||||
| Yes | 1,680 | 7 | 0.91 | 0.39, 2.13 | 33 | 2.72 | 1.70, 4.34 |
| Duration, hours/day | |||||||
| <1 | 994 | 5 | 1.03 | 0.39, 2.76 | 19 | 2.74 | 1.57, 4.79 |
| ≥1 | 458 | 2 | 0.96 | 0.22, 4.15 | 10 | 2.88 | 1.38, 6.01 |
| P for trend | 0.95 | 0.0057 | |||||
| Exposure location | |||||||
| Home | 1,243 | 7 | 1.11 | 0.47, 2.62 | 28 | 3.03 | 1.84, 4.99 |
| Other | 695 | 0 | 11 | 2.61 | 1.32, 5.20 | ||
Abbreviations: CI, confidence interval; OR, odds ratio; PPROM, preterm premature rupture of membranes.
a Less than 32 weeks of gestation.
b Adjusted for maternal age, educational level, employment status, parity, history of preterm delivery, and cesarian delivery.
DISCUSSION
To our knowledge, the present study is the first to comprehensively examine the association between passive smoking and the risk of preterm birth by various clinical subtypes among Chinese nonsmokers. It supports the hypothesis that exposure to passive smoking is associated with an increased risk of very preterm birth and that risk increases with increasing duration of exposure. Similar patterns were observed between medically indicated and spontaneous preterm births.
Previous studies investigating the association between passive smoking and preterm birth provided conflicting results (8–21). Comparison of results from these studies is a challenge because passive smoking was inconsistently defined and gestational age cut offs varied from study to study. The majority of these studies had limited statistical power because of small numbers (n < 200) of preterm births (9–12, 16, 18, 20, 21). Several larger studies (13–15, 17, 19) reported nonsignificant associations between passive smoking and preterm birth overall, which is consistent with the results of our study. However, none of these studies examined the associations by various clinical subtypes except for a study by Windham et al. (14), in which the authors reported a 2-fold increase in the risk of a preterm birth with a gestational age less 35 completed weeks in women exposed to passive smoking.
Our study found that passive smoking was associated with a slight, though nonsignificant, increased risk of preterm birth overall. However, when data were stratified by gestational age, passive smoking was strongly associated with very preterm birth (<32 weeks of gestation) but not moderate preterm birth (32–36 weeks of gestation). Several studies of active maternal smoking also reported a stronger association with very preterm birth than with moderate preterm birth (6, 27–30). Very preterm births account for 1%–2% of all births but more than 50% of neonatal deaths (31), which suggests that very preterm birth is a severe and distinctive clinical subtype of preterm birth that may have a different etiological profile and be more susceptible to the effects of active and passive smoking exposure.
There is no consensus about whether medically indicated and spontaneous preterm births should be grouped together or evaluated separately in studies of etiology (32). Conditions that motivate medically indicated preterm birth (e.g., preeclampsia, placental abruption, and restricted fetal growth) are also strong predictors of spontaneous preterm birth (33–35), and these conditions share mechanisms such as inflammation and vascular compromise that can lead to spontaneous preterm birth (32, 36). On the other hand, spontaneous onset of labor and membrane rupture appears clinically distinctive from fetal distress or severe hypertension that must be managed by early delivery. In our study, we found similar associations for both medically indicated and spontaneous preterm births. The risks of both medically indicated and spontaneous very preterm births were associated with exposure to passive smoking. However, the risk of spontaneous very preterm delivery was limited to women without PPROM. Although chance findings cannot be ruled out because of the small numbers of very preterm births without PPROM, this result may suggest that the effects of passive smoking on very preterm delivery are not due to premature rupture of membrane. Early studies have provided controversial results linking smoking and PPROM (37–39).
Exposure to smoking later in pregnancy is generally considered to be more strongly associated with low birth weight than is exposure during early pregnancy (40). It is unclear whether exposures during different trimesters differentially impact the risk of preterm birth. Although our study showed that exposures to passive smoking anytime during pregnancy increased risk of very preterm birth, exposure to passive smoking in each trimester was not mutually exclusive. There were high correlations of exposures to passive smoking between the 3 trimesters. Nicotine was found to cause a substantial decrease in the mitotic potential of cytotrophoblasts in vitro testing. This effect was also observed in women who smoked (41), which suggests a mechanism for abnormal placental development during early pregnancy (42) because ischemic placental disease is known to lead to preterm birth (43).
Our study also found that exposure to passive smoking at home but not in other locations was associated with the risk of very preterm birth. Although the risk of very preterm birth without PPROM showed a significant association with exposure at both work and other locations, the association was much stronger for passive smoking at home. These findings may indicate that there is a greater exposure to smoke from smokers at home compared with at work or in other public areas. Because the mean duration of exposure to passive smoking was lower at home (0.65 hours/day) compared with that at other locations (1.46 hours/day) in our study, one possible explanation for the observed association could be that smoke concentrations are higher at home than at other locations. This may be because homes generally have a more confined spaces and less efficient ventilation mechanisms than do work places and/or public areas. One early study reported a positive association between children born small for gestational age and passive smoking at home but not at other locations (21). Because several comparisons have been made and the numbers were small for the stratified analyses, these findings could be due to chance.
Unlike another study (8) that reported an 80% increased risk of preterm birth associated with passive smoking among women who were 30 years of age or older and no association between passive smoking and preterm birth among those who were younger than 30 years of age, we did not find that age was an effect modifier. Because information on passive smoking was based on self-report and the majority of women were interviewed after delivery (83.4% among women with term deliveries and 89.4% among women with preterm deliveries), it is possible that women who had a preterm delivery were more likely to underreport the duration of exposure to passive smoking because of the negative connotations associated with smoking around pregnant women. Studies have also suggested that self-reported exposure to passive smoking tends to be underreported (44, 45), resulting in the misclassification of exposed women as unexposed. If any potential biases were present, the association was likely underestimated. Two earlier studies examined the relationship between preterm birth and passive smoking using maternal hair nicotine levels (9, 11), a valid biomarker for measuring chronic exposure to passive smoke (11, 46, 47). Both studies found that high hair nicotine levels were associated with an increased risk of preterm birth and also saw a strong correlation between self-reported passive smoking and hair nicotine levels (9, 11). Another study found no association between salivary nicotine levels and preterm birth, but the study had limited statistical power (20 miscarriage and preterm cases and 13 controls) (48). In addition, a significant association was observed for very preterm birth but not moderate preterm birth, which suggests that differential recall did not affect our findings. The study population was recruited from the largest maternity and child care hospital in Lanzhou, the capital city of Gansu Province. Although the study was a hospital-based study, which might impact generalizability, the rate of preterm births (10.0%) in our study population was within the range of the reported preterm birth rate (4.1%–18.9%) in other Chinese populations, as reviewed by Blencowe et al. (4).
The present study excluded both current and former smokers, minimizing potential differences in health effects of active versus passive smokers. All study participants were Chinese, minimizing differences in genetic susceptibility to passive smoking by ethnic group. We collected and controlled for detailed information on potential confounding factors in the analysis. Information on birth outcomes and maternal complications during pregnancy was obtained from medical records, which minimized misclassification.
In conclusion, our study found that passive smoking was significantly associated with an increased risk of very preterm birth. Because an increased risk was seen for both medically indicated and spontaneous very preterm births but not for medically indicated or spontaneous moderate preterm births, more studies are needed to understand the mechanism by which nicotine influences the in utero developmental processes. Our findings indicate a strong need for public health campaigns to increase awareness of the negative health effects of passive smoking, especially during pregnancy, to protect the health of women and infants.
ACKNOWLEDGMENTS
Author affiliations: Gansu Provincial Maternity and Child Care Hospital, Lanzhou, China (Jie Qiu, Xiaochun He, Hongmei Cui, Chong Zhang, Honghong Zhang, Yun Dang, Xudong Han, Ya Chen, Zhongfeng Tang, Hanru Zhang, Haiya Bai, Ruifeng Xu, Daling Zhu, Xiaojuan Lin, Ling Lv, Xiaoying Xu, Ru Lin, Tingting Yao, Jie Su, Xiaohui Liu, Wendi Wang, Yueyuan Wang, Bin Ma, Sufen Liu, Qing Liu); Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut (Huang Huang, Catherine Lerro, Nan Zhao, Jiaxin Liang, Yawei Zhang); Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut (Shuangge Ma); and Department of Pediatrics, School of Medicine, Yale University, New Haven, Connecticut (Richard A. Ehrenkranz).
Q.L. and Y.Z. contributed equally to this work.
This work was supported by internal funding from the Gansu Provincial Maternity and Child Care Hospital, the Fogarty International Center, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (grant K02HD70324).
We thank all the study personnel from the Gansu Provincial Maternity and Child Care Hospital for their exceptional efforts on study subject recruitment.
Conflict of interest: none declared.
REFERENCES
- 1.Buhimschi CS, Rosenberg VA, Dulay AT, et al. Multidimensional system biology: genetic markers and proteomic biomarkers of adverse pregnancy outcome in preterm birth. Am J Perinatol. 2008;25(3):175–187. doi: 10.1055/s-2008-1061497. [DOI] [PubMed] [Google Scholar]
- 2.Lawn JE, Cousens S, Zupan J. 4 million neonatal deaths: when? Where? Why? Lancet. 2005;365(9462):891–900. doi: 10.1016/S0140-6736(05)71048-5. [DOI] [PubMed] [Google Scholar]
- 3.Mwaniki MK, Atieno M, Lawn JE, et al. Long-term neurodevelopmental outcomes after intrauterine and neonatal insults: a systematic review. Lancet. 2012;379(9814):445–452. doi: 10.1016/S0140-6736(11)61577-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Blencowe H, Cousens S, Oestergaard MZ, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet. 2012;379(9832):2162–2172. doi: 10.1016/S0140-6736(12)60820-4. [DOI] [PubMed] [Google Scholar]
- 5.March of Dimes, PMNCH, Save the Children, WHO. Geneva, Switzerland: World Health Organization; 2012. Born Too Soon: The Global Action Report on Preterm Birth. [Google Scholar]
- 6.Kyrklund-Blomberg NB, Cnattingius S. Preterm birth and maternal smoking: risks related to gestational age and onset of delivery. Am J Obstet Gynecol. 1998;179(4):1051–1055. doi: 10.1016/s0002-9378(98)70214-5. [DOI] [PubMed] [Google Scholar]
- 7.Meeker JD, Benedict MD. Infertility, pregnancy loss and adverse birth outcomes in relation to maternal secondhand tobacco smoke exposure. Curr Womens Health Rev. 2013;9(1):41–49. doi: 10.2174/1573404811309010003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Ahluwalia IB, Grummer-Strawn L, Scanlon KS. Exposure to environmental tobacco smoke and birth outcome: increased effects on pregnant women aged 30 years or older. Am J Epidemiol. 1997;146(1):42–47. doi: 10.1093/oxfordjournals.aje.a009190. [DOI] [PubMed] [Google Scholar]
- 9.Ashford KB, Hahn E, Hall L, et al. The effects of prenatal secondhand smoke exposure on preterm birth and neonatal outcomes. J Obstet Gynecol Neonatal Nurs. 2010;39(5):525–535. doi: 10.1111/j.1552-6909.2010.01169.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Hanke W, Kalinka J, Florek E, et al. Passive smoking and pregnancy outcome in central Poland. Hum Exp Toxicol. 1999;18(4):265–271. doi: 10.1191/096032799678840020. [DOI] [PubMed] [Google Scholar]
- 11.Jaakkola JJ, Jaakkola N, Zahlsen K. Fetal growth and length of gestation in relation to prenatal exposure to environmental tobacco smoke assessed by hair nicotine concentration. Environ Health Perspect. 2001;109(6):557–561. doi: 10.1289/ehp.01109557. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Luo YJ, Wen XZ, Ding P, et al. Interaction between maternal passive smoking during pregnancy and CYP1A1 and GSTs polymorphisms on spontaneous preterm delivery. PLoS One. 2012;7(11):e49155. doi: 10.1371/journal.pone.0049155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Ward C, Lewis S, Coleman T. Prevalence of maternal smoking and environmental tobacco smoke exposure during pregnancy and impact on birth weight: retrospective study using Millennium Cohort. BMC Public Health. 2007;7:81. doi: 10.1186/1471-2458-7-81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Windham GC, Hopkins B, Fenster L, et al. Prenatal active or passive tobacco smoke exposure and the risk of preterm delivery or low birth weight. Epidemiology. 2000;11(4):427–433. doi: 10.1097/00001648-200007000-00011. [DOI] [PubMed] [Google Scholar]
- 15.Fortier I, Marcoux S, Brisson J. Passive smoking during pregnancy and the risk of delivering a small-for-gestational-age infant. Am J Epidemiol. 1994;139(3):294–301. doi: 10.1093/oxfordjournals.aje.a116997. [DOI] [PubMed] [Google Scholar]
- 16.Goel P, Radotra A, Singh I, et al. Effects of passive smoking on outcome in pregnancy. J Postgrad Med. 2004;50(1):12–16. [PubMed] [Google Scholar]
- 17.Jaddoe VW, Troe EJ, Hofman A, et al. Active and passive maternal smoking during pregnancy and the risks of low birthweight and preterm birth: the Generation R Study. Paediatr Perinat Epidemiol. 2008;22(2):162–171. doi: 10.1111/j.1365-3016.2007.00916.x. [DOI] [PubMed] [Google Scholar]
- 18.Lazzaroni F, Bonassi S, Manniello E, et al. Effect of passive smoking during pregnancy on selected perinatal parameters. Int J Epidemiol. 1990;19(4):960–966. doi: 10.1093/ije/19.4.960. [DOI] [PubMed] [Google Scholar]
- 19.Martin TR, Bracken MB. Association of low birth weight with passive smoke exposure in pregnancy. Am J Epidemiol. 1986;124(4):633–642. doi: 10.1093/oxfordjournals.aje.a114436. [DOI] [PubMed] [Google Scholar]
- 20.Mathai M, Vijayasri R, Babu S, et al. Passive maternal smoking and birthweight in a south Indian population. Br J Obstet Gynaecol. 1992;99(4):342–343. doi: 10.1111/j.1471-0528.1992.tb13736.x. [DOI] [PubMed] [Google Scholar]
- 21.Sadler L, Belanger K, Saftlas A, et al. Environmental tobacco smoke exposure and small-for-gestational-age birth. Am J Epidemiol. 1999;150(7):695–705. doi: 10.1093/oxfordjournals.aje.a010072. [DOI] [PubMed] [Google Scholar]
- 22.Leonardi-Bee J, Smyth A, Britton J, et al. Environmental tobacco smoke and fetal health: systematic review and meta-analysis. Arch Dis Child Fetal Neonatal Ed. 2008;93(5):F351–F361. doi: 10.1136/adc.2007.133553. [DOI] [PubMed] [Google Scholar]
- 23.World Health Organization. Preterm Birth, Fact sheet No. 363. http://www.who.int/mediacentre/factsheets/fs363/en/ Updated November 2012. Accessed August 20, 2013.
- 24.Qian J, Cai M, Gao J, et al. Trends in smoking and quitting in China from 1993 to 2003: National Health Service Survey data. Bull World Health Organ. 2010;88(10):769–776. doi: 10.2471/BLT.09.064709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.American College of Obstetricians and Gynecologists. ACOG committee opinion no. 560: Medically indicated late-preterm and early-term deliveries. Obstet Gynecol. 2013;121(4):908–910. doi: 10.1097/01.AOG.0000428648.75548.00. [DOI] [PubMed] [Google Scholar]
- 26.Spong CY, Mercer BM, D'Alton M, et al. Timing of indicated late-preterm and early-term birth. Obstet Gynecol. 2011;118(2 pt 1):323–333. doi: 10.1097/AOG.0b013e3182255999. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Ancel PY, Saurel-Cubizolles MJ, Di Renzo GC, et al. Very and moderate preterm births: are the risk factors different? Br J Obstet Gynaecol. 1999;106(11):1162–1170. doi: 10.1111/j.1471-0528.1999.tb08142.x. [DOI] [PubMed] [Google Scholar]
- 28.Burguet A, Kaminski M, Abraham-Lerat L, et al. The complex relationship between smoking in pregnancy and very preterm delivery. Results of the Epipage Study. BJOG. 2004;111(3):258–265. doi: 10.1046/j.1471-0528.2003.00037.x. [DOI] [PubMed] [Google Scholar]
- 29.Peacock JL, Bland JM, Anderson HR. Preterm delivery: effects of socioeconomic factors, psychological stress, smoking, alcohol, and caffeine. BMJ. 1995;311(7004):531–535. doi: 10.1136/bmj.311.7004.531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Shiono PH, Klebanoff MA, Rhoads GG. Smoking and drinking during pregnancy. Their effects on preterm birth. JAMA. 1986;255(1):82–84. [PubMed] [Google Scholar]
- 31.Goldenberg RL, Rouse DJ. Prevention of premature birth. N Engl J Med. 1998;339(5):313–320. doi: 10.1056/NEJM199807303390506. [DOI] [PubMed] [Google Scholar]
- 32.Savitz DA, Dole N, Herring AH, et al. Should spontaneous and medically indicated preterm births be separated for studying aetiology? Paediatr Perinat Epidemiol. 2005;19(2):97–105. doi: 10.1111/j.1365-3016.2005.00637.x. [DOI] [PubMed] [Google Scholar]
- 33.Ananth CV, Berkowitz GS, Savitz DA, et al. Placental abruption and adverse perinatal outcomes. JAMA. 1999;282(17):1646–1651. doi: 10.1001/jama.282.17.1646. [DOI] [PubMed] [Google Scholar]
- 34.Ananth CV, Savitz DA, Luther ER, et al. Preeclampsia and preterm birth subtypes in Nova Scotia, 1986 to 1992. Am J Perinatol. 1997;14(1):17–23. doi: 10.1055/s-2007-994090. [DOI] [PubMed] [Google Scholar]
- 35.Hediger ML, Scholl TO, Schall JI, et al. Fetal growth and the etiology of preterm delivery. Obstet Gynecol. 1995;85(2):175–182. doi: 10.1016/0029-7844(94)00365-K. [DOI] [PubMed] [Google Scholar]
- 36.Klebanoff MA, Shiono PH. Top down, bottom up and inside out: reflections on preterm birth. Paediatr Perinat Epidemiol. 1995;9(2):125–129. doi: 10.1111/j.1365-3016.1995.tb00126.x. [DOI] [PubMed] [Google Scholar]
- 37.Ekwo EE, Gosselink CA, Woolson R, et al. Risks for premature rupture of amniotic membranes. Int J Epidemiol. 1993;22(3):495–503. doi: 10.1093/ije/22.3.495. [DOI] [PubMed] [Google Scholar]
- 38.Mercer BM, Goldenberg RL, Meis PJ, et al. The Preterm Prediction Study: prediction of preterm premature rupture of membranes through clinical findings and ancillary testing. The National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network. Am J Obstet Gynecol. 2000;183(3):738–745. doi: 10.1067/mob.2000.106766. [DOI] [PubMed] [Google Scholar]
- 39.England MC, Benjamin A, Abenhaim HA. Increased risk of preterm premature rupture of membranes at early gestational ages among maternal cigarette smokers. Am J Perinatol. 2013;30(10):821–826. doi: 10.1055/s-0032-1333408. [DOI] [PubMed] [Google Scholar]
- 40.Lieberman E, Gremy I, Lang JM, et al. Low birthweight at term and the timing of fetal exposure to maternal smoking. Am J Public Health. 1994;84(7):1127–1131. doi: 10.2105/ajph.84.7.1127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Genbacev O, McMaster MT, Lazic J, et al. Concordant in situ and in vitro data show that maternal cigarette smoking negatively regulates placental cytotrophoblast passage through the cell cycle. Reprod Toxicol. 2000;14(6):495–506. doi: 10.1016/s0890-6238(00)00107-6. [DOI] [PubMed] [Google Scholar]
- 42.Lindbohm ML, Sallmén M, Taskinen H. Effects of exposure to environmental tobacco smoke on reproductive health. Scand J Work Environ Health. 2002;28(suppl 2):84–96. [PubMed] [Google Scholar]
- 43.Ananth CV, Vintzileos AM. Maternal-fetal conditions necessitating a medical intervention resulting in preterm birth. Am J Obstet Gynecol. 2006;195(6):1557–1563. doi: 10.1016/j.ajog.2006.05.021. [DOI] [PubMed] [Google Scholar]
- 44.DeLorenze GN, Kharrazi M, Kaufman FL, et al. Exposure to environmental tobacco smoke in pregnant women: the association between self-report and serum cotinine. Environ Res. 2002;90(1):21–32. doi: 10.1006/enrs.2001.4380. [DOI] [PubMed] [Google Scholar]
- 45.Rauh VA, Whyatt RM, Garfinkel R, et al. Developmental effects of exposure to environmental tobacco smoke and material hardship among inner-city children. Neurotoxicol Teratol. 2004;26(3):373–385. doi: 10.1016/j.ntt.2004.01.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Al-Delaimy WK, Crane J, Woodward A. Is the hair nicotine level a more accurate biomarker of environmental tobacco smoke exposure than urine cotinine? J Epidemiol Community Health. 2002;56(1):66–71. doi: 10.1136/jech.56.1.66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Pichini S, Garcia-Algar O, Muñoz L, et al. Assessment of chronic exposure to cigarette smoke and its change during pregnancy by segmental analysis of maternal hair nicotine. J Expo Anal Environ Epidemiol. 2003;13(2):144–151. doi: 10.1038/sj.jea.7500264. [DOI] [PubMed] [Google Scholar]
- 48.Arffin F, Al-Bayaty FH, Hassan J. Environmental tobacco smoke and stress as risk factors for miscarriage and preterm births. Arch Gynecol Obstet. 2012;286(5):1187–1191. doi: 10.1007/s00404-012-2417-0. [DOI] [PMC free article] [PubMed] [Google Scholar]