Article

Smoking in Pregnant Women Screened for an Opioid Agonist Medication Study Compared to Related Pregnant and Non-Pregnant Patient Samples

Department of Psychiatry, Johns Hopkins University, Baltimore, Maryland, USA.
The American Journal of Drug and Alcohol Abuse (Impact Factor: 1.47). 09/2009; 35(5):375-80. DOI: 10.1080/00952990903125235
Source: PubMed

ABSTRACT Little is known about the prevalence and severity of smoking in pregnant opioid dependent patients.
To first characterize the prevalence and severity of smoking in pregnant patients screened for a randomized controlled trial, Maternal Opioid Treatment: Human Experimental Research (MOTHER), comparing two agonist medications; and second, to compare the MOTHER screening sample to published samples of other pregnant and/or patients with substances use disorders.
Pregnant women (N = 108) screened for entry into an agonist medication comparison study were retrospectively compared on smoking variables to samples of pregnant methadone-maintained patients (N = 50), pregnant opioid or cocaine dependent patients (N = 240), non-pregnant methadone-maintained women (N = 75), and pregnant non-drug-addicted patients (N = 1,516).
Of screened patients, 88% (n = 95) smoked for a mean of 140 months (SD = 79.0) starting at a mean age of 14 (SD = 3.5). This rate was similar to substance use disordered patients and significantly higher compared to general pregnant patients (88% vs. 22%, p < .001).
Aggressive efforts are needed to reduce/eliminate smoking in substance-abusing pregnant women.

Download full-text

Full-text

Available from: Peter Robert Martin, Aug 30, 2015
1 Follower
 · 
152 Views
  • Source
    • "The percentage of opioid-dependent pregnant participants in this study who reported current cigarette smoking was 95%, more than four times higher than in the general pregnant population (Jones et al., 2009; Tong et al., 2009). This high rate of cigarette smoking is alarming because continued smoking during pregnancy is associated with diverse adverse health effects (Cnattingius, 2004). "
    [Show abstract] [Hide abstract]
    ABSTRACT: INTRODUCTION: Little is known about the relationship between cigarette smoking and agonist treatment in opioid-dependent pregnant patients. The objective of this study is to examine the extent to which cigarette smoking profiles differentially changed during the course of pregnancy in opioid-dependent patients receiving either double-blind methadone or buprenorphine. Patients were participants in the international, randomized controlled Maternal Opioid Treatment: Human Experimental Research (MOTHER) study. METHODS: A sample of opioid-maintained pregnant patients (18-41 years old) with available smoking data who completed a multisite, double-blind, double-dummy, randomized controlled trial of methadone (n = 67) and buprenorphine (n = 57) between 2005 and 2008. Participants were compared on smoking variables based on opioid agonist treatment condition. RESULTS: Overall, 95% of the sample reported cigarette smoking at treatment entry. Participants in the two medication conditions were similar on pretreatment characteristics including smoking rates and daily cigarette amounts. Over the course of the pregnancy, no meaningful changes in cigarette smoking were observed for either medication condition. The fitted difference in change in adjusted cigarettes per day between the two conditions was small and nonsignificant (β = -0.08, SE = 0.05, p = .132). CONCLUSIONS: Results support high rates of smoking with little change during pregnancy among opioid-dependent patients, regardless of the type of agonist medication received. These findings are consistent with evidence that suggests nicotine effects, and interactions may be similar for buprenorphine compared with methadone. The outcomes further highlight that aggressive efforts are needed to reduce/eliminate smoking in opioid-dependent pregnant women.
    Nicotine & Tobacco Research 01/2013; 15(7). DOI:10.1093/ntr/nts274 · 2.81 Impact Factor
  • Source
    • "The percentage of opioid-dependent pregnant participants in this study who reported current cigarette smoking was 95%, more than four times higher than in the general pregnant population (Jones et al., 2009; Tong et al., 2009). This high rate of cigarette smoking is alarming because continued smoking during pregnancy is associated with diverse adverse health effects (Cnattingius, 2004). "
    [Show abstract] [Hide abstract]
    ABSTRACT: AIMS: To investigate whether cigarette smoking and/or depression contribute to neonatal abstinence syndrome (NAS) severity. DESIGN: Cohort study analyzing data from a randomized, controlled trial of methadone versus buprenorphine. SETTING: Seven study sites that randomized patients to study conditions and provided comprehensive addiction treatment to pregnant patients. PARTICIPANTS: 119 of 131 opioid-dependent pregnant patients who completed the MOTHER study. MEASUREMENTS: Smoking data and depression status were obtained from the Addiction Severity Index and Mini International Neuropsychiatric Interview, respectively. Neonatal outcomes (birth weight, preterm delivery and NAS pharmacologic treatment) were collected from the medical charts. Study site was a fixed-effect factor in all analyses. FINDINGS: Cigarette smoking was reported by 94% of participants and depression identified in 35%. Smoking was associated with low birth weight, preterm delivery, and NAS pharmacologic treatment in both depressed and non-depressed participants. The association between smoking and NAS treatment differed significantly between depressed and non-depressed participants. Among non-depressed participants, adjusting for site and illicit drug use, each additional average cigarette per day (CPD) increased the odds of NAS treatment by 12% [95%CI: (1.02-1.23), p=0.02]. Among depressed participants, each additional average CPD did not statistically increase the odds of NAS treatment [OR: 0.94, 95% CI: (0.84-1.04), p=0.23]. CONCLUSIONS: These results are consistent with the hypothesis that NAS expression is influenced by many factors. The relationship between CPD and NAS pharmacologic treatment is attenuated among depressed women in this study for reasons currently unknown. Further investigations are needed to clarify the complex relationships among maternal smoking, depression, and NAS.
    Addictive Disorders & Their Treatment 12/2011; 10(4):180-187. DOI:10.1097/ADT.0b013e31821cadbd
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Opiates, cocaine, and metabolites were quantified by liquid chromatography-mass spectrometry (LC-MS) in 284 urine specimens, collected thrice weekly, to monitor possible drug relapse in 15 pregnant heroin-dependent women. Opiates were detected in 149 urine specimens (52%) with limits of quantification (LOQ) of 10-50 microg/L. Morphine, morphine-3-glucuronide, and/or morphine-6-glucuronide were positive in 121 specimens; 6-acetylmorphine, a biomarker of heroin ingestion, was quantifiable in only 7. No heroin, 6-acetylcodeine, papaverine, or noscapine were detected. One hundred and sixty-five urine specimens (58%) from all 15 participants were positive for one or more cocaine analytes (LOQ 10-100 microg/L). Ecgonine methylester (EME) and/or benzoylecgonine were the major cocaine biomarkers in 142. Anhydroecgonine methylester, a biomarker of smoked cocaine, was positive in six; cocaethylene and/or ecgonine ethylester, biomarkers of cocaine and ethanol co-ingestion, were found in 25. At the current Substance Abuse Mental Health Services Administration cutoffs for total morphine (2000 microg/L), codeine (2000 microg/L), 6-acetylmorphine (10 microg/L), and benzoylecgonine (100 microg/L), 16 opiate- and 29 cocaine-positive specimens were identified. Considering 100 microg/L EME as an additional urinary cocaine biomarker would identify 51 more positive cocaine specimens. Of interest is the differential pattern of opiate and cocaine biomarkers observed after LC-MS as compared to gas chromatography-mass spectrometry analysis.
    Journal of analytical toxicology 01/2010; 34(1):17-25. DOI:10.1093/jat/34.1.17 · 2.63 Impact Factor
Show more