Maternal tobacco use: A third-trimester risk factor for small-for-gestational-age pregnancy outcome.

BACKGROUND: Small for gestational age (SGA) is a well-known consequence of maternal smoking. Here, we newly examine the magnitude of SGA risk by week of gestational age. METHODS: Singleton live births (N = 3,032,928) with recorded birth weight, gestational age (22-44 weeks), and maternal tobacco use (Y/N) were categorized as to SGA (Y/N), based on 10th percentile gender-specific weights-for-age. RESULTS: SGA prevalence among tobacco users (19.5%) and non-users (9.1%) yielded a significant SGA prevalence rate ratio of 2.15 (2.13-2.16) and a significant adjusted odds ratio of 2.36 (2.34-2.38). The tobacco non-users' rate was steadily near 9% across the week 22-44 gestational age range. The tobacco users' rate was steady until week 33 when it rose monotonically through week 37 to about 20% at week 38 and remained high. This pattern for SGA by gestational week was similar for prevalence rates and adjusted ORs. Tobacco use only through week 33 was not seen to be an SGA risk factor. The magnitude of tobacco use as an SGA risk factor for late third trimester births increased during the period of preterm birth and became fully evident with a two-fold risk for full term infants. CONCLUSION: We newly report the temporal pattern of tobacco-related SGA by week of gestational age. Tobacco-related SGA was only seen for late third trimester births - increasing during weeks 33-37 with a doubling during weeks 38-44. This pattern, informative for issues of mechanism, highlights the potential benefit of extending tobacco cessation programs through the third trimester of pregnancy.

Small-for-gestational age prevalence risk factors in central Appalachian states with mountain-top mining.

OBJECTIVES: To identify risk factors for small-for-gestational age (SGA) for counties in central Appalachian states (Kentucky (KY), Tennessee (TN), Virginia (VA), and West Virginia (WV)) with varied coal mining activities. MATERIAL AND METHODS: Live birth certificate files (1990-2002) were used for obtaining SGA prevalence rates for mothers based on the coal mining activities of their counties of residence, mountain-top mining (MTM) activities, underground mining activities but no mountain-top mining activity (non-MTM), or having no mining activities (non-mining). Co-variable information, including maternal tobacco use, was also obtained from the live birth certificate. Adjusted odds ratios were obtained using multivariable logistic regression comparing SGA prevalence rates for counties with coal mining activities to those without coal mining activities and comparing SGA prevalence rates for counties with coal mining activities for those with and without mountain-top mining activities. Comparisons were also made among those who had reported tobacco use and those who had not. RESULTS: Both tobacco use prevalence and SGA prevalence were significantly greater for mining counties than for non-mining counties and for MTM counties than for non-MTM counties. Adjustment for tobacco use alone explained 50% of the increased SGA risk for mining counties and 75% of the risk for MTM counties, including demographic pre-natal care co-variables that explained 75% of the increased SGA risk for mining counties and 100% of the risk for MTM. The increased risk of SGA was limited to the third trimester births among tobacco users and independent of the mining activities of their counties of residence. CONCLUSIONS: This study demonstrates that the increased prevalence of SGA among residents of counties with mining activity was primarily explained by the differences in maternal tobacco use prevalence, an effect that itself was gestational-age dependent. Self-reported tobacco use marked the population at the increased risk for SGA in central Appalachian states. Int J Occup Med Environ Health 2018;31(1):11-23.

Arsenic in Drinking Water and Lung Cancer Mortality in the United States: An Analysis Based on US Counties and 30 Years of Observation (1950-1979).

Background. To examine whether the US EPA (2010) lung cancer risk estimate derived from the high arsenic exposures (10-934 µg/L) in southwest Taiwan accurately predicts the US experience from low arsenic exposures (3-59 µg/L). Methods. Analyses have been limited to US counties solely dependent on underground sources for their drinking water supply with median arsenic levels of ≥3 µg/L. Results. Cancer risks (slopes) were found to be indistinguishable from zero for males and females. The addition of arsenic level did not significantly increase the explanatory power of the models. Stratified, or categorical, analysis yielded relative risks that hover about 1.00. The unit risk estimates were nonpositive and not significantly different from zero, and the maximum (95% UCL) unit risk estimates for lung cancer were lower than those in US EPA (2010). Conclusions. These data do not demonstrate an increased risk of lung cancer associated with median drinking water arsenic levels in the range of 3-59 µg/L. The upper-bound estimates of the risks are lower than the risks predicted from the SW Taiwan data and do not support those predictions. These results are consistent with a recent metaregression that indicated no increased lung cancer risk for arsenic exposures below 100-150 µg/L.

What HIV programs work for adolescent girls?

BACKGROUND: Adolescent girls face unique challenges in reducing their risk of acquiring HIV because of gender inequalities, but much of HIV programming and evaluation lacks a specific focus on female adolescents. METHODS: This article, based on a review of 150 studies and evaluations from 2001 to June 2013, reviews evidence on programming for adolescents that is effective for girls or could be adapted to be effective for girls. RESULTS: The evidence suggests specific interventions for adolescent girls across 3 critical areas: (1) an enabling environment, including keeping girls in school, promoting gender equity, strengthening protective legal norms, and reducing gender-based violence; (2) information and service needs, including provision of age-appropriate comprehensive sex education, increasing knowledge about and access to information and services, and expanding harm reduction programs for adolescent girls who inject drugs; and (3) social support, including promoting caring relationships with adults and providing support for adolescent female orphans and vulnerable children. DISCUSSION: Numerous gaps remain in evidence-based programming for adolescent girls, including a lack of sex- and age-disaggregated data and the fact that many programs are not explicitly designed or evaluated with adolescents in mind. However, evidence reinforces bolstering critical areas such as education, services, and support for adolescent girls. CONCLUSIONS: This article contributes to the growing body of literature on HIV and adolescent girls and reviews the vulnerabilities of girls, articulates the challenges of programming, develops a framework for addressing the needs of girls, and reviews the evidence for successful programming for adolescent girls.