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Results for “Socioeconomic Factors”

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At least 19 recordsLinked to original sources
PubMed1989

Maternal mortality in Jamaica. Socioeconomic factors.

Socioeconomic factors relating to all maternal deaths identified during the 12 months of the Jamaican Perinatal Morbidity and Mortality Survey were compared with a control population of over 10,000 women. The maternal mortality rate was 11.5 per 10,000 livebirths. Initial analyses revealed (a) that the risk of maternal death declined with increasing maternal education level, (b) that mothers who lived in households with direct pumped water and/or flush toilets enjoyed a reduced risk; (c) mothers who were themselves the major wage earner and (d) those living in households where the major wage earner and source of income was an agricultural worker or farmer were at increased risk of maternal death. A previous analysis showed that the mother's age, her parity and variables indicating access to medical care were important. Logistic regression showed that only maternal age and toilet facilities were independently associated with maternal mortality.

Female↗
PubMed2001

Depressive symptoms in middle-aged women are more strongly associated with physical health and social support than with socioeconomic factors.

The association of socioeconomic factors, health-related factors, and social support with depressive symptoms has been extensively studied. However, most epidemiological studies have focused on a few factors such as marital status, social class, and employment. In this study of middle-aged women we analyzed both univariate and multivariate associations of socioeconomic factors, perceived physical health factors, and social support with self-rated depressive symptoms measured with the Beck Depression Inventory. A nationwide sample (n = 1851) of Finnish women aged 48-50 years was analyzed. Socioeconomic, health-related, and social support factors were all measured with single items. All variables, except level of urbanization, were significantly associated with depressive symptoms in univariate analyses. Multivariate associations were examined with standard multiple regression analyses in three stages: first with the socioeconomic factors, then with socioeconomic and health factors, and finally entering the social support factors into the regression model. In the first model, being either on a sick leave or at home as working status, being divorced, and having low income reached significance. In the second model, being divorced and having poor perceived physical health were the most powerful among the five significant variables. In the last model, explaining 32% of the variance, the most powerful predictors of depressive symptoms were perceived current physical health, satisfaction with received social support, and quality of intimate relationships. For the prevention or intervention of depressive symptoms among middle-aged women in the population subjects with concurrent subjective or objective health problems and poor social support seem to comprise a particularly important target group.

Depression↗
PubMed2006

Lumbar disc disorders and low-back pain: socioeconomic factors and consequences.

Socioeconomic factors are important risk factors for lumbar pain and disability. The total costs of low-back pain in the United States exceed $100 billion per year. Two-thirds of these costs are indirect, due to lost wages and reduced productivity. Each year, the fewer than 5% of the patients who have an episode of low-back pain account for 75% of the total costs. Because indirect costs rely heavily on changes in work status, total costs are difficult to calculate for many women and students as well as elderly and disabled patients. These methodologic challenges notwithstanding, the toll of lumbar disc disorders is enormous, underscoring the critical importance of identifying strategies to prevent these disorders and their consequences.

Adolescent↗
PubMed1997

Visual impairment and socioeconomic factors.

BACKGROUND: Information about socioeconomic factors associated with visual impairment can assist in the design of intervention programmes. Such information was collected by the Melbourne Visual Impairment Project (Melbourne VIP). METHODS: The Melbourne VIP was a population based study of non-institutionalised permanent residents in nine suburbs of the Melbourne metropolitan area aged 40 years of age and older. A standardised eye examination was provided to eligible residents which included a structured interview. Variables of interest for this analysis were age, sex, country of birth, language spoken at home, education level, use of private health insurance, employment status, and living arrangements. Visual impairment was defined as a best corrected visual acuity < 6/18 and/or visual field constriction to within 20 degrees of fixation. RESULTS: A total of 3271 (83%) residents participated. Participants ranged in age from 40 to 98 years; 54% were female. Forty four (1.34%) were classified as visually impaired due to visual acuity and/or visual field loss. To evaluate the independent association of the significant sociodemographic variables with visual impairment, a regression model was constructed that included age, retirement status, use of private health insurance, and household arrangement. The results showed that age was the significant predictor of visual impairment (OR: 3.19; CI: 2.29-4.43), with the mean age of people with visual impairment significantly older (75.0 years) compared with people without visual impairment (58.2 years) (t test = 9.71; p = 0.0001). Of the 44 visually impaired people, 39 (87%) were aged 60 years of age and older. CONCLUSION: The results indicate that age is the most significant factor associated with visual impairment. Of some importance was the finding that people with visual impairment were less likely to have private health insurance. With the aging of the population, the number of people affected by visual impairment will increase significantly. Intervention programmes need to be established before the onset of middle age to offset the escalation of visual impairment in the older population.

Adult↗
PubMed1991

The relationship between socioeconomic factors and pulmonary tuberculosis.

UNLABELLED: The role of socioeconomic factors for the risk of developing tuberculosis (TB) is unclear. Differences and similarities between cases and controls on various socioeconomic factors were determined. Some 84 black TB patients on ambulatory treatment and 84 disease-free controls living in the same urban area (South Africa) and matched for age and sex were studied. VARIABLES MEASURED: demographic details, general living conditions, household ownership of luxury items, and weekly consumption of four proteins (meat, fish, chicken and cheese). Three socioeconomic indices were constructed from the above variables. No significant differences were found between cases and controls on most of the variables. Overall significant differences were found on the pattern of language groups (chi-square; p = 0.031), employment groups (chi-square; p = 0.029) and meat (chi-square; p = 0.012) and chicken consumption (chi-square; p = 0.034). A tendency was observed for more employed cases than controls to have a primary school education. However, no conclusive evidence was found on the association between socioeconomic factors and risk of developing TB. The development of a more appropriate socioeconomic measure for developing countries is a necessary step for further research.

Adolescent↗
PubMed2005

Space-time models with time-dependent covariates for the analysis of the temporal lag between socioeconomic factors and lung cancer mortality.

The relationship between socioeconomic factors and mortality for lung cancer is investigated. To identify the proper lag time between socioeconomic factors and lung cancer mortality, a space-time hierarchical Bayesian model with time-dependent covariates is adopted. A real example on lung cancer mortality, males, in Tuscany (Italy) during the period 1971-1999, is provided. Results confirm the presence of an association between mortality for lung cancer and socioeconomic factors with a temporal lag (latency time) of at least 10 years.

Adolescent↗
PubMed1989

Malnutrition and child mortality: are socioeconomic factors important?

The influences of household economic condition, maternal education, sex, and nutritional status of children on mortality were examined using multivariate analytical techniques. Weights of around 1700 children aged 2 60 months in five villages of Matlab, Bangladesh, were taken during the first half of 1981. The children were followed for 18 months and their survival was recorded. The severely malnourished children had a risk of death nine times that of their counterparts with better nutritional status. Female children had a higher risk of death than the males. Mother's education and economic condition of household also showed negative relationships with the risk of death, but the effect of mother's education was modified by economic condition and sex of the children.

Bangladesh↗
PubMed2006

[Study on the relationship between childhood obesity and various determinants, including socioeconomic factors, in an urban area].

OBJECTIVES: This study was conducted to investigate the prevalence of childhood obesity, the association between the undesirable lifestyles and socioeconomic factors, the association between childhood obesity and various risk factors, including socioeconomic factors, and the agreement between the body mass index (BMI) classification and the body fat percentage. METHODS: The study subjects were all the 5th grade students from all the elementary schools in Gunpo City, Kyunggi Province, South Korea (4043 children at 22 schools). The subjects were measured for their height, weight and percent body fat etc. and they were also surveyed by questionnaire from March 18th to April 25th, 2005. To determine whether the children were within normal limits or not, standardized BMIs for each age group were used. The data was analyzed by logistic regression analysis using SAS 9.0 version. RESULTS: The prevalence of childhood obesity prevalence was 25.1%. Boys had a higher prevalence of obesity (27.5%) than did the girls (22.5%). Children had tendencies of having undesirable lifestyles and getting obese if they had a lower socioeconomic status. The risk factors for childhood obesity were low paternal education (OR: 1.17, 95% CI: 0.97-1.42) and non-parental caregivers (OR: 1.34, 95% CI: 0.98-1.82). Other risk factors for childhood obesity were a high birth-weight, longer TV/computer-using time, a lower fruit-eating frequency, short sleeping hours and parental obesity. The agreement rate between the BMI classification and the body fat percentage was 93.1%. CONCLUSIONS: This study showed the children had a higher prevalence of obesity: further, not only individual lifestyles, but also socioeconomic factors could influence childhood obesity. Childhood obesity was especially more problematic for children with a low socioeconomic status.

Body Height↗
PubMed1992

Socioeconomic factors affecting the longevity of the Japanese population: a study for 1980 and 1985.

The effects of urbanisation, low income and rejuvenation of the population on life expectancy at birth and at 20, 40 and 65 years of age for males and females in Japan were examined twice, in 1980 and 1985. For males, urbanisation was the major factor determining life expectancy at birth and at age 20 years, and low income was the key determinant of decreased life expectancy except at 65 years of age. For females high income was the factor significantly decreasing life expectancy at 65 years of age in 1980, and rejuvenation of the population inversely influenced life expectancy except at birth in 1985. Life expectancy for all age groups in 1985 was significantly longer than in 1980 for both males and females.

Adult↗
PubMed1982

National estimates of blood lead levels: United States, 1976-1980: association with selected demographic and socioeconomic factors.

Data from the second National Health Nutrition Examination Survey showed that 22 per cent of persons six months through 75 years old had blood lead levels under 10 micrograms per deciliter; 1.9 per cent had elevated levels (greater than or equal to 30 micrograms per deciliter [greater than or equal to 1.45 mumol per liter]). Among children six months through five years old the prevalence of elevated levels was significantly higher (4 per cent) than previously predicted on the basis of fewer data. The prevalence of elevated lead levels was 12.2 per cent in black children and 2.0 per cent in white children. Mean levels of blood lead were higher in blacks than white among children and adults, among young children living in urban and rural areas, and among members of low-income, moderate-income, and higher-income families. These racial contrasts may reflect different lead exposure or absorption (or both). Young children from families (both white and black) whose incomes were under $6,000 had a significantly higher prevalence of elevated lead levels than those from households with incomes of $6,000 or more.

Adolescent↗
PubMed1979

The association of obesity with socioeconomic factors in Missouri.

The prevalence of obesity and underweight was estimated for residents of Missouri more than 9 years old on the basis of age, sex, household income, educational attainment, and population density from the results of a survey conducted in 1973. The incidence of overweight was greatest among children 10 to 16 years old and the least for adults 17 to 35 years old. Four percent of the girls 10 to 16 were greater than 159% of average weight for height. Among women greater than 59 years old the incidence of overweight and underweight were high. The proportion of adult women who were overweight as defined by average weight for height and body mass index (W/H2) was inversely related to household income and education. The same was true for adult men in relation to income but the reverse results were observed for education. A larger proportion of urban men were overweight as defined by body mass index compared to rural men. The incidence of obesity among males of all ages and females greater than 59 years old appeared to be related to residence in specific types of communities.

Adolescent↗