0115 966 7955 Today's Opening Times 10:00 - 20:00 (GMT)
Place an Order
Instant price

Struggling with your work?

Get it right the first time & learn smarter today

Place an Order
Banner ad for Viper plagiarism checker

Impact of Social Determinants on Health

Disclaimer: This work has been submitted by a student. This is not an example of the work written by our professional academic writers. You can view samples of our professional work here.

Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UK Essays.

Published: Wed, 04 Oct 2017

Song et al (2011) studied the influence of social determinants of health on disease rates. They specified AIDS as the disease of concern and utilized data from American Community Survey. They used correlation and partial correlation coefficients quantify the effect of socioeconomic determinants on AIDS diagnosis rates in certain areas and found that the AIDS diagnosis rate was mutually related with kind, marital status and population density. Poverty, education level and unemployment also determine the cause of disease in an individual.

In developed and developing countries socioeconomic status proved to be an important cause of cardiovascular disease. Survey studies showed that education was the most important socioeconomic determinant in relation to cardiovascular risk factor. Smoking was also a major cause of cardiovascular disease. Low socioeconomic status had a direct relationship with higher levels of cardiovascular risk factors (Yu et al, 2000; Reddy et al, 2002; Jeemon & Reddy, 2010; Thurston et al, 2005; Janati et al, 2011 and Lang et al, 2012).

Lantz et al (1998) investigated the impact of education, income and health behaviors on the risk of dying within the next 7.5 years with longitudinal survey study. The results of cross tabulation showed that the mortality rate has a strong association with education and income.

Habib et al (2012) conducted a questionnaire based survey to measure the social, economic, demographic and geographic influence on the disease of bronchial asthma in Kashmir valley. After analysis in SPSS they concluded that non smokers, males working in farms and females working with animals have a high incidence of Bronchial Asthma. The study also showed a significant relationship between the age and disease.

Arif and Naheed (2012) used “The Pakistan Social and Living Standard Measurement Survey 2004-05” conducted by the Federal Bureau of Statistics to determine the socioeconomic, demographic, environmental and geographical factors of diarrhea morbidity among the sampled children. Their study found a relationship between diarrhea morbidity and economic factors particularly ownership of land, livestock and housing conditions. Child’s gender and age, total number of children born, mother’s age and education and sources of drinking water did show significant effect on the diarrhea morbidity among children.

Aranha et al (2011) conducted a survey in Brazil’s district São Paulo, to determine the association between children’s respiratory diseases reported by parents, attendance at school, parents’ educational level, family income and socioeconomic status. By applying chi square test they concluded that the health of children is associated with parents’ higher education, particularly mothers. Family income, analyzed according to per capita income did not affect the number of reports of respiratory diseases from parents.

Deolalikar and Laxminarayan (2000) used data from 1997 Cambodia Socioeconomic Survey to estimate the influence of socioeconomic variables on the extent of disease transmission within villages in Cambodia. They concluded that infectious diseases were the leading cause of morbidity in the country. Younger adults were less likely to get infected by others, but it increased with age. Income and the availability of a doctor had a significant effect on disease transmission.

Survey studies based on different countries showed a strong association between socioeconomic factors (income, education and occupational position) and obesity. After analysis there was a significant effect of consumption of low quality food due to economic factors on increased obesity. For men, both the highest level of occupational position and general education completed were found to have a significant effect on obesity while women in the lowest income group were three times as likely to be obese as women in the highest income group (Kuntz and Lampert, 2010; Akil and Ahmad, 2011 and Larsen et al, 2003).

Yin et al (2011) used data from the 2007 China Chronic Disease Risk Factor Surveillance of 49,363 Chinese men and women aged 15-69 years to examine the association between the prevalence of self-reported physician diagnosed Chronic Obstructive Pulmonary Disease (COPD) and socioeconomic status defined by both educational level and annual household income. Multivariable logistic regression modeling was performed. Among nonsmokers, low educational level and household income were associated with a significant higher prevalence of COPD.

Siponen et al (2011) tried to study the relationship between the health of Finnish children under 12 years of age and parental socioeconomic factors (educational level, household income and working status) by conducting population based survey. The analysis was done by using Pearson’s Chi-Square tests, and logistic regression analysis with 95% confidence intervals. The results showed that parental socioeconomic factors were not associated with the health of children aged under 12 years in Finland.

Washington State Department of Health (2007) examined Washington adults and inferred that adults with lower incomes or less education were more likely to smoke, obessed, or ate fewer fruits and vegetables than adults with the broader culture, higher incomes and more education. In cultures where smoking was culturally unacceptable for women, women died less often from smoking-related diseases than women in groups where smoking was socially accepted. Lack of access to or inadequate use of medical services, contributed to relatively poorer health among people. In lower socioeconomic position groups health care received by the poor was inferior in quality. People of higher socioeconomic position had larger networks of social support. Low levels of social capital had been associated with higher mortality rates. People who experienced racism were more likely to have poor mental health and unhealthy lifestyles.

Hosseinpoor et al (2012) took self-reported data, stratified by sex and low or middle income, from 232,056 adult participants in 48 countries, derived from the 2002–2004 World Health Survey. A Poisson regression model with a robust variance and cross tabulations were used deducing the following results. Men reported higher prevalence than women for current daily smoking and heavy episodic alcohol drinking, and women had higher growth of physical inactivity. In both sexes, low fruit and vegetable consumption were significantly higher.

Braveman (2011) concluded that there was a strong relationship between income, education and health. Health was improved if income or education increased. Stressful events and circumstances followed a socioeconomic incline, decreased as income increased.

Lee (1997) examined the effects of age, nativity, population size of place of residence, occupation, and household wealth on the disease and mortality experiences of Union army recruits while in service using Logistic regression. The patterns of mortality among recruits were different from the pattern of mortality among civilian populations. Wealth had a significant effect only for diseases on which nutritional influence was definite. Migration spread communicable diseases and exposed newcomers to different disease environments, which increased morbidity and mortality rate.

Ghias et al (2012) studied the patients having HCV positive living in province of Punjab, Pakistan. Socio-demographic factors and risk factors were sought out using questionnaire. Logistic regression and artificial neural network methods were applied and found that patient’s education, patient’s liver disease history, family history of hepatitis C, migration, family size, history of blood transfusion, injection’s history, endoscopy, general surgery, dental surgery, tattooing and minor surgery by barber were 12 main risk factors that had significant influence on HCV infection.

REFERENCES

  1. Song, R. et al (2011) “Identifying The Impact Of Social Determinants Of Health On Disease Rates Using Correlation Analysis Of Area-Based Summary Information” Public Health Reports Supplement 3, Volume 126, 70-80.
  2. Yu, Z. et al (2000) “Associations Between Socioeconomic Status And Cardiovascular Risk Factors In An Urban Population In China” Bulletin of the World Health Organization Volume 78, No. 11, 1296-1305.
  3. Reddy, K. et al (2002) ” Socioeconomic Status And The Prevalence Of Coronary Heart Disease Risk Factors” Asia Pacific J Clin Nutr Volume 11, No. 2, 98–103.
  4. Jeemon, P. & Reddy, K. (2010) ”Social Determinants Of Cardiovascular Disease Outcomes In Indians” Indian J Med Res Volume 132, 617-622.
  5. Thurston, R. et al (2005) “Is The Association Between Socioeconomic Position And Coronary Heart Disease Stronger In Women Than In Men?” American Journal of Epidemiology Volume 162, No. 1, 57-65.
  6. Janati, A. et al (2011) “Socioeconomic Status and Coronary Heart Disease” Health Promotion Perspectives Volume 1, No. 2, 105-110.
  7. Lang, T. et al (2012) “Social Determinants Of Cardiovascular Diseases” Public Health Reviews Volume 33, No. 2, 601-622.
  8. Lantz, P. et al (1998) “Socioeconomic Factors, Health Behaviors, and Mortality” JAMA Volume 279, No. 21, 1703-1708.
  9. Habib, A. et al (2012) “Socioeconomic, Demographic and Geographic Influence on Disease Activity of Bronchial Asthma in Kashmir Valley” IOSR Journal of Dental and Medical Sciences (JDMS) ISSN: 2279-0853, ISBN: 2279-0861, Volume 2, No. 6, 04-07.
  10. Arif, A. and Naheed, R. (2012) “Socio-Economic Determinants Of Diarrhoea Morbidity In Pakistan” Academic Research International ISSN-L: 2223-9553, ISSN: 2223-9944 ISSN-L: 2223-9553, ISSN: 2223-9944, Volume 2, No. 1, 490-518.
  11. Aranha, M. et al (2011) “Relationship Between Respiratory Tract Diseases Declared By Parents And Socioeconomic And Cultural Factors” Rev Paul Pediatr Volume 29, No. 3, 352-356.
  12. Deolalikar , A. and Laxminarayan, R. (2000) “Socioeconomic Determinants of Disease Transmission in Cambodia” Resources for the Future Discussion Paper, 00–32.
  13. Kuntz, B. and Lampert, T. (2010) “Socioeconomic Factors and Obesity” Deutsches Ärzteblatt International Volume 107, No. 30, 517-22.
  14. Akil, L. and ; Ahmad, H. (2011) “Effects Of Socioeconomic Factors On Obesity Rates In Four Southern States And Colorado” Ethnicity & Disease Volume 21, 58-62.
  15. Larsen, P. et al (2003) “The Relationship of Ethnicity, Socioeconomic Factors, and Overweight in U.S.Adolescents”OBESITY RESEARCH Volume 11, No.1, 121-129.
  16. Yin, P. et al (2011) “Prevalence Of COPD And Its Association With Socioeconomic Status In China: Findings From China Chronic Disease Risk Factor Surveillance 2007” BMC Public Health Volume 11, 586-593.
  17. Siponen, M. et al (2011) “Children’s Health And Parental Socioeconomic Factors: A Population-Based Survey In Finland” BMC Public Health Volume 11, 457-464.
  18. Washington State Department of Health (2007) “Social and Economic Determinants of Health” The Health of Washington State Volume 1, No. 3, 01-07.
  19. Hosseinpoor, A. et al (2012) “Socioeconomic inequalities in risk factors for noncommunicable diseases in low-income and middle income countries: results from the World Health Survey” BMC Public Health Volume 12, 912-924.
  20. Braveman, P. (2011) “Accumulating Knowledge on the Social Determinants of Health and Infectious Disease” Public Health Reports Supplement 3, Volume 126, 28-30.
  21. Lee, C. (1997) “Socioeconomic Background, Disease, and Mortality among Union Army Recruits: Implications for Economic and Demographic History” Explorations in Economic History Volume 34, 27-55.
  22. Ghias, M. et al (2012) “Statistical Modelling and Analysis of Risk Factors for Hepatitis C Infection in Punjab, Pakistan” World Applied Sciences Journal Volume 20, No. 2, 241-252.

To export a reference to this article please select a referencing stye below:

Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.

Request Removal

If you are the original writer of this essay and no longer wish to have the essay published on the UK Essays website then please click on the link below to request removal:


More from UK Essays