"Reducing Secondhand Smoke on Children" is a perfect example of a paper on child development. The analysis will focus on finding the correlation between congestion and exposure of secondhand smoke (SHS) on children. The analysis shall be based on the results obtained from various sources. According to Ö berg et. al. (2011), at least 40% of those affected by SHS were children followed by females at 35% and lastly males at 33%. There were at least 379,000 deaths globally because of diseases resulting from SHS. The disturbing results were that 47% of these deaths occurred in children.
Children are definitely at higher risk of SHS diseases and deaths as compared to adults. Statistics also show that SHS affects different demographic variables differently. For example, the children from the white race exhibited high exposure at 99%, the blacks 96%, Hispanic 73%, and other 64%. The interpretation for these statistics may be the whites constitute the highest number of smokers. The analysis will examine the race/ethnicity to see the correlation. In accordance with location, the blacks living in apartments and detached premises exhibited the same rate of exposure whereas the white rates lowered for those in detached premises (Wilson et.
al. , 2011). The rate of smoking between individuals living in poverty and those above the poverty line was 29.2% and 16.2% respectively (Schmidt, 2015). This shows that children from poor communities have a high rate of exposure to SHS due to their existing environment (Tarvernise & Gebeloff, 2014). The study will focus on race, the economic status of the parents, the neighborhood, and government policies. This will give the background information that will help underpin the changing trend of the population which has resulted in high exposure of children to SHS. Plan for Data Analysis of Study Variables The variables in this study will take the form of independent variables i. e.
race and poverty level in relation to measuring how they influence the exposure of SHS to children and the dependent variables. The dependent variables include the increased number of exposure because of government policy, economic status, and poverty level that lead people to smoke. The data obtained shows that SHS is likely to affect children from parents with low income or those living below the poverty level.
This shall be effective because they live in congested premises where there can be a high number of smokers thus increasing the exposure of SHS to the children in this area. Lack of social amenities can lead to early smoking among children due to bad companies that, again, increase the high rate of death in children due to smoking. We can claim that the policies to ban smoking in public areas have consequently shifted smoking back to the home environment thus increasing exposure of the children living within the parameter of the smoker’ s dwelling place (Ö berg et.
al. , 2011). The researcher expects high levels of exposure of SHS on children due to government laxity in imposing stringent laws to curb cigarette and their SHS impact. Laugesen et. al. (2010) was of the view that the trend can stop if the government is committed to intervene in order to reduce the SHS. This may be due to hefty taxes and a reduced production rate for tobacco products. This will lead to scarcity of cigarettes, thus reducing smoking especially amongst the poor who mostly live in congested areas.
Other emerging theories concerning this study may be hiding behind medical cover for tobacco companies by providing coverage funds to treat the effects of smoking i. e. cancer (Hovell & Hughes, 2009). This cover-up is a strategy to ensure that their business is unaffected by retaliation from an angry society.
Hovell, M. F., & Hughes, S. C. (2009). The behavioral ecology of secondhand smoke exposure: A pathway to complete tobacco control. Nicotine & Tobacco Research, 11(11), 1254-64. DOI: 10.1093/ntr/ntp133.
Laugesen, M., Glover, M., Fraser, T., McCormick, R., & Scott, J. (2010). Four policies to end the sale of cigarettes and smoking tobacco in New Zealand by 2020. NZ Med J, 123(1314), 55-65.
Öberg, M., Jaakkola, M. S., Woodward, A., Peruga, A., & Prüss-Ustün, A. (2011). Worldwide burden of disease from exposure to second-hand smoke: A retrospective analysis of data from 192 countries. The Lancet, 377(9760), 139-146.
Schmidt, L. (2015). Tobacco and socioeconomic status. Retrieved from http://www.tobaccofreekids.org/research/factsheets/pdf/0260.pdf
Tarvernise, S. & Gebeloff, R. (2014). Smoking proves hard to shake among the poor. Retrieved from http://ash.org/smoking-proves-hard-to-shake-among-the-poor/
Wilson, K. M., Klein, J. D., Blumkin, A. K., Gottlieb, M., & Winickoff, J. P. (2011). Tobacco-smoke exposure in children who live in multiunit housing. Pediatrics, 127(1), 85-92.