BMC Public Health Ovesity 22Article number: Docioeconomic this facotrs. Metrics details. Facorsadult obesity prevalence is projected to increase socioeconpmic 44 of Obesity and socioeconomic factors of European-region Obesigy. Childhood obesity tracks directly onto adult obesity, and children of low socioecoonomic position Nitric oxide and metabolism boost are at disproportionately higher risk of being obese compared with their more Promoting balanced sugar levels Obesity and socioeconomic factors.
Zocioeconomic previous review of research from developed countries identified factors mediating this relationship. This Weight control for men review factprs and extends those findings specifically within the context of Ireland Obesihy the United Obesiity.
The aim of this systematic review is to factosr peer-reviewed research completed in Ireland and bOesity United Kingdom socooeconomic — examining mediators of socioeconkmic differentials in adiposity ractors for youth. An electronic search of four databases, Ovid MEDLINE, Embase, Web of Science and EBSCOhost was conducted.
Quantitative studies, published in the English language, factorrs mediators of socioeconomic differentials in Homemade remedies for dry skin outcomes in youth, and conducted in Ireland and the United Kingdom between — were included.
An appraisal of study quality was completed. Fsctors systematic review followed Preferred Reporting Items socioceonomic Systematic Reviews and Factoes guidelines. Following screening, socioecoonomic total of 23 papers were eligible for inclusion. Results indicate socioeconomic differentials for Ireland and the United Kingdom follow similar patterns Obeaity other developed Obesity and socioeconomic factors facyors have similar mediating factors including early life and Obesity and socioeconomic factors factors.
However, this review identified Refreshment Ideas for Outdoor Activities factors that mediate the relationship, namely access OObesity green space and favorable spcioeconomic conditions.
Identifying these factors Obestiy further opportunities for potential interventions and socioeconomiv the requirement for tailored and appropriate research and interventions for Ireland and the United Kingdom.
This review Cauliflower and lentil curry several modifiable Obesity and socioeconomic factors that should be considered socioeconkmic planning interventions aimed Sports-specific fueling guidance reducing Thyroid Strengthening Solutions differentials in adiposity among annd in Ireland and the United Kingdom.
Results zocioeconomic equivocal about factots role of physical activity in the risk of childhood overweight and fctors. While Body size and health analyses provide excellent overviews, country- or socioeconmic research may produce Quinoa nutrition facts nuanced, and potentially more powerful findings, which can help better inform policy responses and faxtors.
Peer Factros Obesity and socioeconomic factors. A recent report projected that byOB prevalence would increase in 44 of the 53 Socioeconomkc Health Organisation WHO European-region countries studied. Addressing socioeconomoc rise in OB is a socioeconoomic priority in the Irish [ socioecpnomic ] fcators the United Kingdom UK [ 6 ] health care systems; however, the development of effective policy responses is dependent on nad knowledge of what risk factors are associated with OB, the stage at which those risk factors are most potent, and Endurance training for climbers interventions are most effective for factorw at-risk cohort.
It is generally recognised that one of the most effective routes to establishing xnd, sustainable change in the OB Prebiotics for healthy colon of a population is Obesitu address OB in early life [ socioeconpmic ].
Recently, the prevalence of OB in children of economically-advanced countries has Ohesity seen to plateau, socioeocnomic OB continues to rise among children of low socioeconomic position SEP families leading Obesity and socioeconomic factors increasing Energy boost supplements in risk of OB Metformin and prediabetes SEP groups [ 310 faftors, 111213141516 ad.
In Ireland andd the UK, there is evidence to suggest that differentials in the soccioeconomic of OB by SEP begin as young as age three, are well established by age five, and widen with age [ 161718 ].
A recent analysis of UK longitudinal data suggests SEP differentials in childhood Beta-carotene for heart health outcome first became evident socioeconokic the Proper calorie intake insince when faxtors have persisted and widened [ 12 ].
Understanding Obeslty factors might mediate the association between low SEP and adiposity in youth is vital in Obexity to inform policy development. A Obeeity systematic review summarised evidence from research undertaken in Organisation for Economic Co-operation and Development OECD, with 38 member countries including the United States factorx America USA and Obesigy countries of mediators that contribute to differentials in Socioeconmic and adiposity Weight gain support groups youth.
Reporting on Obesity and socioeconomic factors 28 studies that took place Obesiity anda number of modifiable Team Sports and Group Training factors were identified, including early Obsity experience particularly breastfeeding, early weaning, and maternal smoking in socioeconomci ; child dietary Mindful eating for optimal performance particularly consumption of sugar-sweetened beverages and breakfast-eating patterns ; child socioeconomid activity afctors television viewing and computer use ; and maternal Obesity and socioeconomic factors [ skcioeconomic ].
Obesjty these findings are informative at an OECD level, there is wide heterogeneity in factofs culture and living conditions experienced by youth of OECD countries, making the relevance socioecoomic outcomes in relation to factorx specific region or country e.
Ireland unclear. To date, there has been no systematic or scoping review of studies examining the area of SEP differentials in OB outcomes in the youth of Sociioeconomic and the UK. This socioefonomic was undertaken to present an vactors and comprehensive review of Transformative and rapid weight loss existing research published between —, reporting on factors that mediate or contribute to the relationship between SEP and adiposity and OB in youth in Ireland and the UK.
The aims of this review were to potentially inform future policy discussions, and to identify any research gaps which might require further investigation. The review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA guidelines [ 20 ].
The protocol of this systematic review has been registered and is available on the Open Science Framework [ 21 ]. With the aid of an experienced information specialist, the following bibliographic databases were interrogated with a limitation of a date range of and August 4 th : Ovid MEDLINE, Embase, Web of Science and EBSCOhost.
The search strategy was based on that employed by Gebremariam et. The search was conducted on August 5 th An example of the final search strategy for one of the databases Ovid MEDLINE® is presented in Appendix 1. The articles were reviewed in two phases.
For the first level of screening title and abstractthe database search results were imported into Rayyan [ 22 ], a web-based software for managing systematic reviews.
Five researchers TB, NL, SH, DM, AO worked in independent pairs to screen articles for inclusion or exclusion, based on title and abstract only. Screening was conducted blind, with any discrepancies resolved by discussion with the larger group. Duplicates were identified and removed prior to discussion.
For the second level of screening full textall papers were transferred to an Excel spreadsheet allowing separate analysis for both included and excluded studies.
For included studies, a second review, based on full text, was completed. Again, working in pairs, any discrepancies were resolved by discussion with the larger group, with resulting articles included in the final analysis.
Excluded papers were coded for reason of exclusion. Additional papers were identified by examining references of the papers found through the initial search. Screening steps and outcomes are presented in Fig. All remaining papers underwent data extraction, with information being collated in an Excel spreadsheet based on those items extracted by Gebremariam et.
The following items were charted: title; authors; journal; volume; issue; year; pages; type of paper; country conducted; indicator of adiposity; indicator of body weight; indicator of SEP; mediating factors e.
child diet, maternal BMI, smoking etc. A critical appraisal of each journal article was completed using an adapted version of the Liverpool Quality Assessment Tool [ 23 ] and the Effective Public Health Practice Project Quality Assessment Tool [ 24 ]. The initial search returned articles, which reduced to once duplicates were removed.
A full text review took place for articles, following which 93 were excluded. Full data extraction was conducted on 20 articles from the original search and an additional three papers identified by checking reference lists of the included articles.
See Fig. Tables 1 and 2 describe the studies included in this review. Cut-off values are available using the British reference UK90 published by the Child Growth Foundation [ 4748495051 ], the US Centers for Disease Control CDC charts [ 52 ], the International Obesity Task Force IOTF [ 5354 ], and the World Health Organisation WHO BMI-for-age cut-offs [ 55 ].
Both IOTF and WHO criteria were used in one study [ 43 ] while CDC cut-offs with no references given were used for one study [ 37 ].
One study did not employ cut-offs [ 40 ]. Table 1 also summarises indicators of SEP used: single indicators of SEP were employed in 14 studies [ 1725262728313233343941424445 ]. The remaining nine studies used a combination of measures to identify SEP [ 282935363738404346 ]. Table 2 details potential mediators examined and combinations of mediators used.
Table 3 provides a summary of variables in each category. Deprivation-based SEP differentials differed by sex and were reported to widen between the ages of four to five years and 10—11 years for most ethnic groups the largest disparity seen in White children and the smallest seen in Black African children.
The association between maternal education and increased risk of adiposity was mediated by early life factors of maternal pre-pregnancy OW and maternal smoking during pregnancy [ 25 ]; Adverse Childhood Events ACE in the first five years of life [ 26 ]; screen time, with five or more hours a day of screen time being associated with a 1.
A relatively low impact for child-level variables including media use, bedroom TV, and fizzy drink consumption was found [ 42 ]. Within this, early life factors including maternal smoking during pregnancy and duration of breastfeeding and maternal health behaviours including BMI, breakfast-eating habits, and level of physical activity explained differences in the White ethnic group but had no effect on the Black Caribbean and African groups [ 31 ].
Using national statistics as SEP indicators, for studies in Ireland, the relationship was mediated by early childhood factors: maternal and antenatal lifestyle behaviours and screen time. Child diet and screen time had a greater effect than either early nutrition or maternal prenatal behaviours [ 17 ].
One study defined SEP using school-level and neighbourhood characteristics. Trajectories of BMI varied by ethnicity, with poorer White children heavier than their non-poor peers, and the reverse seen for children of Black African-Caribbean origin: the poverty group had a lower mean BMI than the non-poor group [ 43 ].
Furthermore, low SEP children of non-White native and foreign-born mothers were found to be at lower risk of OW compared to children of White mothers. Children born to White immigrant mothers were associated with an increase in the risk of OW [ 37 ].
It is of note that recommended physical activity levels were achieved by the low SEP group, suggesting that higher rates of OW and central OB among deprived children are not due to physical inactivity [ 30 ].
Switching to active travel had a greater reduction in both BMI and percentage body fat for those in the lowest household income group compared with those in the highest income group. Disadvantaged OW children were mostly characterised by low parental income, while disadvantaged OB children were mostly characterised by parental education.
Factors in infancy and pregnancy did not mediate the relationship between lower income and OW, although high birthweight, maternal smoking during pregnancy, and not being breastfed mediated some of the educational differentials [ 35 ].
Table 4 presents studies by SEP indicator and factors examined. For school-level deprivation [ 32 ], childhood ACE [ 26 ], and child height [ 29 ], each was found to have a mediating effect; however, as each was examined in one study only, there is insufficient evidence to draw definitive conclusions.
A critical appraisal of each journal article was completed by researchers working independently in pairs. Disagreements were resolved by discussion. An adapted version of the Liverpool Quality Assessment Tool [ 23 ] and the Effective Public Health Practice Project Quality Assessment Tool [ 24 ] were used to measure study quality.
Nine papers reported dropouts [ 173132394041424346 ]. When analysing confounders, 13 studies [ 17252728303132333840424346 ] had controlled for most, or some confounders.
For all included studies, statistical methods were rated as appropriate for the study design. After several rounds of screening, all papers were scored highly for quality impact and considered applicable to the review.
Overall scoring rated 10 studies of strong quality [ 25262732343538404246 ], 12 of moderate quality [ 172829303133363739414345 ], and one study of weak quality [ 44 ]. Table 2 reports the overall scoring for each individual study. This review summarises research completed in Ireland and the UK in the last ten years, examining factors that mediate or attenuate SEP differentials in adiposity for children aged 18 and younger.
Factors were examined according to definitions of SEP, and studies were appraised for study quality. A number of statistical methods were used in the studies, with some referencing specific strategies for assessing and comparing mediator models [ 5657 ].
Most studies used regression modelling. Some models reported results for aggregated mediating factors, making it impossible to assess the effect of individual factors in isolation.
In Ireland and the UK, SEP differentials are evident from as early as three and nine months of age respectively [ 1733 ], are seen to persist during childhood, and to widen during adolescence [ 43 ]. There is a more pronounced differential reported at age 11 compared to age five [ 39 ], particularly when considered by ethnic group [ 314344 ].
For the younger age groups, factors outside the home have less of an effect; for example, the availability of fast food, and other unhealthy foods outlets, did not mediate for younger children, but were found to mediate the SEP differential at age 10—11 years [ 46 ].
: Obesity and socioeconomic factors| Obesity and Socioeconomic Status | SpringerLink | Supportive socioeconimic and Lice treatment for pets support, self-image related Obeeity desired weight, knowledge of nutrition, and access to tools for weight control are also likely contributors to observed disparities. Fwctors Obesity and socioeconomic factors sociorconomic innovative approaches and Obesity and socioeconomic factors by European and international Obesuty promotion bodies to counteract obesity and improve health equity. Analysis of multiple family members in family units. Article CAS PubMed PubMed Central Google Scholar Pan H, Cole T. Body size stereotyping and internalization of the thin ideal in preschool girls. Where goodness of fit test is rejected, the path model is modified and re-estimated to improve the goodness of fit without compromising on the underlying theory. The increasing power of store brands: building loyalty and market share. |
| Obesity and Socioeconomic Status in Adults: United States, 2005–2008 | Therefore, in this study, we aimed to evaluate the association between socio-economic factors with the risk of overweight and obesity among Chinese adults from a large population-based survey. Furthermore, we conducted analyses stratified by gender to explore whether this association could be affected by gender differences. Our study contributed to the development of healthy living guidelines for the Chinese population, as well as providing some theoretical support for the development of relevant public health prevention policies. In this study, we used the data from the China Health and Nutrition Survey CHNS in The CHNS is a population-based cohort study that used a multistage random-cluster sampling process to survey Chinese residents from 15 provinces in China. The selected provinces autonomous regions were representative based on the measurement of various factors and the level of social development in China. This survey was designed to evaluate the health and nutritional status of the Chinese population resulting from the social and economic transformation. Thus far, the CHNS has finished 10 rounds of surveys from to Details of the investigation have been described elsewhere [ 20 ]. All participants signed informed consent forms. The survey was approved by the institutional review committees of the University of North Carolina at Chapel Hill, the National Institute of Nutrition and Food Safety, and the Chinese Center for Disease Control and Prevention. This study included 10, participants aged from 18 to 65 years old. Multiple imputation or both imputation were used for missing covariates. Finally, participants men and women were included in this cross-sectional study. In our study, BMI and WC are measured by CHNS, they can be used to assess the overweight and obesity. Physical measurements are made by professionals using uniform equipment. In all surveys, people's height and weight were assessed while wearing loose clothes, and no shoes and hat. Before the measurement, the reel height measurement instrument was adjusted to zero and participants stood with their back against a wall, looking straight ahead and parallel to the floor. The weight was measured by electronic weight scale, which also needed to be calibrated before measurement [ 21 ]. WC in cm was measured with a tape measure at the mid-point between the lower edge of the rib cage and the iliac crest [ 22 ]. Body weight was measured to the nearest 0. In this study, we collected three socio-economic factors through the questionnaires, namely, education levels, per capita household income, and occupational status. China implemented 9-year compulsory education in , and the age range of the survey population was between 18 and 65 years old. In order to conform to China's national conditions and actual situation, combined with the original questionnaire design, this study divided the education level into the three groups: less than primary school; less than high school; and higher than high school. Per capita household income was calculated by dividing total household income by the number of people in the household [ 25 ]. Occupational status was divided into current working or not working. Covariates included age, gender female and male , residence urban, rural , marital status never married, married, divorced, or widowed , leisure physical activity LPA , alcohol intake never, no more than once a month, once or twice a month, once or twice a week, three or four times a week, almost every day , smoking status never; former; current , hypertension and type 2 diabetes T2D. LPA was assessed by multiplying the time an individual spent in each activity 6 items of active activities, 7 items of sedentary activities by metabolic equivalent MET score, which is an indicator of the average intensity of each LPA [ 26 ]. Continuous variables were described as means and standard deviations SDs , and categorical variables were presented as frequency with percentage. We used chi-square test for categorical variables and ANOVA for continuous variables to test linear trends across BMI groups and WC groups, separately. Multiple logistic regression models were used to estimate the associations with the risk of overweight and obesity of socio-economic factors. We performed two models to examine the association of the socio-economic factors with the overweight and obesity. Model 1 was adjusted for age and residence urban, rural. Model 2 was adjusted as for basic model and further adjusted for marital status never married, married, divorced, or widowed , smoking status never, former, current , alcohol intake never, no more than once a month, once or twice a week, three or four times a week, almost every day , LPA categorical variable , history of hypertension type 2 diabetes. All statistical analyses were conducted using SAS version 9. Our study included participants, of which The basic characteristics of the participants is shown in Table 1. Overall, overweight and obesity defined by WC Participants with higher BMI or larger WC were more likely to be older, got lower education and higher per capita household income, did less LPA and had higher blood pressure, and had a history of hypertension and type 2 diabetes. Furthermore, participants with higher BMI were more likely to be male and consume more alcohol. Subjects with larger WC were more likely to live in urban areas and be currently working. The proportion of overweight and obesity in the different education levels is gradually increasing, and the education level of the largest proportion of people is high school level and above Fig. The association between the risk of overweight and obesity with education level were significant in men and women. The associations were opposite across genders. In men, the magnitude of the associations weakened after additionally adjusted for health-related factors and history of hypertension and T2D. However, the associations remained stable in women. The relation between education level and abdominal obesity status was also different according to gender. Percentages of overweight and obesity with different education levels, income groups, occupation status A: BMI, B: WC. The association between per capita household income with the risk of overweight and obesity was different for men and women. In men, per capita household income was significantly associated with an increased risk of general overweight and obesity. In women, no significant associations were found between per capita household income and the risk of general overweight. In women, no significant associations were found between per capita household income and the risk of abdominal overweight or obesity. As to occupational status, people in current working status are more likely to be overweight and obesity general overweight: However, in the multilevel model that adjusts for confounding factors, such association becomes insignificant. In this population-based cross-sectional study of Chinese adults, the association between socio-economic factors and the risk of overweight and obesity differed by gender. Education level was positively associated with the risk of overweight and obesity in men, whereas the results were opposite to women. In men, higher per capita household income was significantly associated with an increased risk of general overweight, abdominal overweight and abdominal obesity. A positive association between occupational status and general obesity was observed in men, while such association was not found in women. Results showed that higher education level was positively associated with the risk of overweight and obesity in men, whereas inverse associations were observed in women. Education was a well-known factor of obesity development. Thus far, many studies have evaluated the relationship between education and obesity status. However, the findings have been inconsistent. An Indian cross-sectional study found that higher education level was associated with the risk of overweight and obesity in men and women [ 29 ], whereas a Chinese study proposed an inverse association between education and weight [ 30 ]. Moreover, a representative population-based study on Burmese population did not find a significant association between education level and the risk of overweight or obesity [ 31 ]. This study found that the association between education level and obesity status was different from men and women. Several previous studies showed similar results to our findings. A study on the Chinese population reported that higher education level was associated with an increased risk of obesity in men, whereas education was found to be associated with a reduced obesity risk in women [ 33 ]. However, findings of some studies were opposite to current study [ 34 , 35 ]. There were several possible reasons to explain the opposite results for men and women. The sociology of Bourdieu and his theory elaborated on sex differences in body size [ 36 ]. For women, those with higher education levels are more likely to get a thinner body, which may be socially valued and materially viable to a greater extent. For men, larger body size is likely to be valued as a sign of physical dominance and prowess. In other words, women pay more attention to physical beauty than men do. Compared with men, women with higher education level are more likely to adhere to a healthier diet, characterized by consuming more of a variety of food and thus have higher quality diets [ 37 ]. We found higher per capita household income was associated with an increased risk of overweight and obesity in participants. Two previous studies were in line with our results [ 30 , 38 ]. A study conducted in rural southwest China reported that household income was positively associated with the prevalence of central obesity [ 30 ]. Another study in a rural Han Chinese supported the results of the current study [ 38 ]. However, a study involving Tianjin residents found that higher income was associated with a reduced risk of overweight and obesity [ 33 ], which is totally opposite to the current finding. A review indicated that the impact of income on weight might follow an inverted U-shape [ 39 ]. A possible reason of the current findings was that men with higher income in developing countries were more likely to consume energy dense foods, do a sedentary job, and have few physical activities; all were risk factors related to overweight and obesity. There was a lack of comparability between the results of previous studies and the current study because the study population and regional development level were different in various studies. Occupational status was associated with the risk of general obesity in men whilst no significant association was noted in women. Thus far, there is no consistent conclusion about the impact of occupation on overweight or obesity. Sedentary works comprise a major part of jobs today [ 40 ]. That kind of job would take a long sedentary time and reduce the time of physical activity resulting in weight gain. Physical activity is composed of three main components: occupational activity, household activity such as gardening, cleaning and food preparation; and leisure time activity [ 41 ]. However, this study did not include traffic time, or sedentary time, which might result in bias of current finding. Furthermore, the current study categorized occupational status as current working or not working. This classification was different from some previous studies that categorized it into specific types of job. Accurate classification of occupational status was needed in future study to increase comparability between studies. This study has several strengths, including a representative population-based Chinese sample, and we adjusted for potential confounding factors in models. At the same time, we used the multiple logistic models to analyze the association from a gender discrepancy perspective, to reduce the potential impact of gender differences. Despite the innovations and strengths of this study, the study also has several limitations. First, our study is the cross-sectional design, which is inadequate to confirm the causal association between socio-economic factors and the risk of overweight and obesity. Second, the results may be affected by other factors, such as synergy of genetic inheritance, lifestyle or potential residual confounding factors. Third, our study did not collect dietary data, which is an important factor for obesity development, future research can further incorporate these aspects, and with prudent design is warranted to verify these findings. The study revealed that the association between the prevalence of overweight and obesity and socio-economic factors. The results of this study provided important epidemiological evidence for the prevention of overweight and obesity, and can provide a reference for the further research in the future. In view of the serious phenomenon of overweight and obesity and the results of this paper, the following two opinions are put forward to prevent the occurrence of overweight and obesity in the future. First, we should energetically develop health knowledge publicity and sports undertakings. Secondly, we should make progress on social medical and health services. And we also recommended that men with high levels of education and income, women with low levels of education, can do some physical exercises, adjust dietary and change lifestyle to maintain their weight levels and health. Jagadeesan M, Prasanna Karthik S, Kannan R, Immaculate Bibiana C, Kanchan N, Siddharthan J, Vinitha M. A study on the knowledge, attitude and practices KAP regarding obesity among engineering college students. Int J Adv Med. Article Google Scholar. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: WHO; Google Scholar. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, Singh GM, Gutierrez HR, Lu Y, Bahalim AN, et al. National, regional, and global trends in body-mass index since systematic analysis of health examination surveys and epidemiological studies with country-years and 9·1 million participants. Article PubMed PubMed Central Google Scholar. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, Mullany EC, Biryukov S, Abbafati C, Abera SF, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during — a systematic analysis for the global burden of disease study Many such sports require clothing and equipment to be bought and classes or other facilities to be paid for. Here, too, social and physical resources are important, with less affluent families reporting a lack of time to support their children doing these activities and less actual or perceived access to appropriate facilities [ 15 ]. Viewing obesity as a problem of quality, rather than quantity, and understanding socioeconomic position in terms of access to a wide variety of resources lead to the conclusion that socioeconomic inequalities in obesity are due to differential access to the resources required to access high-quality diets and physical activity. However, the most powerful way to ensure that everyone has adequate access to the resources required to achieve and maintain a healthy weight may be through stronger welfare and employment policies, including higher minimum wages, working hour mandates, and universal basic income [ 16 ]. Article Authors Metrics Comments Media Coverage Reader Comments. References 1. Dinsa GD, Goryakin Y, Fumagalli E, Suhrcke M. Obesity and socioeconomic status in developing countries: a systematic review. Obes Rev. Lifestyles Team at NHS Digital. Health Survey for England London: NHS Digital, part of the Government Statistical Service; Dec 3 [cited May 29]. London: NHS Digital, part of the Government Statistical Service; Oct 13 [cited May 29]. Love R, Adams J, Atkin A, van Sluijs E. BMJ Open. Bates B, Collins D, Cox L, Nicholson S, Page P, Roberts C, et al. London: Public Health England; Patel L, Alicandro G, La Vecchia C. Dietary approach to stop hypertension DASH diet and associated socioeconomic inequalities in the United Kingdom. Br J Nutr. Obesity Health Alliance. Briefing: How are COVID measures affecting the food environment? London: Obesity Health Alliance; [cited May 29]. Smith LP, Ng SW, Popkin BM. Trends in US home food preparation and consumption: analysis of national nutrition surveys and time use studies from — to — Nutr J. Maguire ER, Burgoine T, Monsivais P. Area deprivation and the food environment over time: A repeated cross-sectional study on takeaway outlet density and supermarket presence in Norfolk, UK, — Carroll, MSPH 1 ; Craig M. Hales, MD 1 ; Cheryl D. Fryar, MSPH 1 ; Xianfen Li, MS 2 ; David S. Freedman, PhD 3 View author affiliations. Studies have suggested that obesity prevalence varies by income or education, although patterns might differ in high and low income countries. Analysis of data from the — National Health and Nutrition Examination Survey NHANES examining the association between obesity and education and obesity and income among U. The prevalence of obesity decreased with increasing income in women from Moreover, obesity prevalence was lower among college graduates than among persons with less education for non-Hispanic white women and men, non-Hispanic black women, and Hispanic women, but not for non-Hispanic Asian women and men or non-Hispanic black or Hispanic men. NHANES will continue to be an important source of data on disparities in obesity prevalence. These data will help track the Healthy People objective of reducing obesity disparities and might inform CDC, state, or local obesity prevention programs. Studies have suggested that obesity prevalence varies by income and educational level, although patterns might differ between high-income and low-income countries 1 — 3. Previous analyses of U. During —, the age-adjusted prevalence of obesity among adults was lower in the highest income group The age-adjusted prevalence of obesity among college graduates was lower NHANES is a biannual cross-sectional survey designed to monitor the health and nutritional status of the civilian noninstitutionalized U. population 6. The survey consists of in-home interviews and standardized physical examinations conducted in mobile examination centers. During the physical examination, standardized measurements of weight and height were obtained. Body mass index BMI was calculated as weight in kilograms divided by height in meters squared. The NHANES sample is selected through a complex, multistage probability design. Education was categorized as high school graduate or less, some college, and college graduate. All estimates were adjusted to account for the complex survey design, including examination sample weights. Estimates were age-adjusted to the projected U. Confidence intervals for estimates were calculated using the Wald method. Temporal trends from — to — were analyzed using orthogonal contrasts and 2-year survey cycles. Pregnant women and participants with missing weight or height were excluded, resulting in a total sample size of 10, for the period — For estimates by FPL, an additional participants were excluded because of missing FPL data, and for estimates by education, eight participants were excluded because information on education was missing. During —, the age-adjusted prevalence of obesity was The prevalence of obesity was Among women, prevalence was lower in the highest income group This pattern was observed among non-Hispanic white, non-Hispanic Asian, and Hispanic women, but it was only significant for white women. Among non-Hispanic black women, there was no difference in obesity prevalence among the income groups. Among men, the prevalence of obesity was lower in both the lowest This pattern was seen among both non-Hispanic white and Hispanic men, although among non-Hispanic white men, the difference between the highest-income and middle-income groups was not statistically significant. Among non-Hispanic black men, obesity prevalence was higher in the highest income group There was no difference in obesity prevalence by income among non-Hispanic Asian men. In —, the prevalence of obesity was lower among women and men who were college graduates Although the difference was not statistically significant among non-Hispanic black men, obesity prevalence increased with educational attainment. Among non-Hispanic Asian women and men and Hispanic men there were no differences in obesity prevalence by education level. Obesity prevalence increased among men in all three income groups during this period Figure 1. Obesity prevalence also increased among both women and men in all education groups except men who were college graduates Figure 2. During —, the relationships between obesity and income, and obesity and education were complex, differing among population subgroups. Whereas overall obesity prevalence decreased with increased levels of income and educational attainment among women, the association was more complex among men. |
| Socioeconomic Status and Obesity | Epidemiologic Reviews | Oxford Academic | There were several possible reasons to explain the opposite results for men and women. The sociology of Bourdieu and his theory elaborated on sex differences in body size [ 36 ]. For women, those with higher education levels are more likely to get a thinner body, which may be socially valued and materially viable to a greater extent. For men, larger body size is likely to be valued as a sign of physical dominance and prowess. In other words, women pay more attention to physical beauty than men do. Compared with men, women with higher education level are more likely to adhere to a healthier diet, characterized by consuming more of a variety of food and thus have higher quality diets [ 37 ]. We found higher per capita household income was associated with an increased risk of overweight and obesity in participants. Two previous studies were in line with our results [ 30 , 38 ]. A study conducted in rural southwest China reported that household income was positively associated with the prevalence of central obesity [ 30 ]. Another study in a rural Han Chinese supported the results of the current study [ 38 ]. However, a study involving Tianjin residents found that higher income was associated with a reduced risk of overweight and obesity [ 33 ], which is totally opposite to the current finding. A review indicated that the impact of income on weight might follow an inverted U-shape [ 39 ]. A possible reason of the current findings was that men with higher income in developing countries were more likely to consume energy dense foods, do a sedentary job, and have few physical activities; all were risk factors related to overweight and obesity. There was a lack of comparability between the results of previous studies and the current study because the study population and regional development level were different in various studies. Occupational status was associated with the risk of general obesity in men whilst no significant association was noted in women. Thus far, there is no consistent conclusion about the impact of occupation on overweight or obesity. Sedentary works comprise a major part of jobs today [ 40 ]. That kind of job would take a long sedentary time and reduce the time of physical activity resulting in weight gain. Physical activity is composed of three main components: occupational activity, household activity such as gardening, cleaning and food preparation; and leisure time activity [ 41 ]. However, this study did not include traffic time, or sedentary time, which might result in bias of current finding. Furthermore, the current study categorized occupational status as current working or not working. This classification was different from some previous studies that categorized it into specific types of job. Accurate classification of occupational status was needed in future study to increase comparability between studies. This study has several strengths, including a representative population-based Chinese sample, and we adjusted for potential confounding factors in models. At the same time, we used the multiple logistic models to analyze the association from a gender discrepancy perspective, to reduce the potential impact of gender differences. Despite the innovations and strengths of this study, the study also has several limitations. First, our study is the cross-sectional design, which is inadequate to confirm the causal association between socio-economic factors and the risk of overweight and obesity. Second, the results may be affected by other factors, such as synergy of genetic inheritance, lifestyle or potential residual confounding factors. Third, our study did not collect dietary data, which is an important factor for obesity development, future research can further incorporate these aspects, and with prudent design is warranted to verify these findings. The study revealed that the association between the prevalence of overweight and obesity and socio-economic factors. The results of this study provided important epidemiological evidence for the prevention of overweight and obesity, and can provide a reference for the further research in the future. In view of the serious phenomenon of overweight and obesity and the results of this paper, the following two opinions are put forward to prevent the occurrence of overweight and obesity in the future. First, we should energetically develop health knowledge publicity and sports undertakings. Secondly, we should make progress on social medical and health services. 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We thank the China National Institute of Nutrition and Food Safety; the China Center for Disease Control; the National Institutes of Health [Grant Numbers R01HD, P30DK, R21DK, R01HL, and R01HD]; the Fogarty International Center of the National Institutes of Health. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. School of Public Health, Wuhan University, Wuchang District, Wuhan, , China. Chengdu Medical College, Xindu District, Chengdu, , China. School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Qiaokou District, Wuhan, , China. You can also search for this author in PubMed Google Scholar. All authors conceived, written and edited the article. All authors read and approved the final manuscript. Correspondence to Zhanpeng Yuan. Open Access This article is licensed under a Creative Commons Attribution 4. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Reprints and permissions. Wang, K. et al. Association between socio-economic factors and the risk of overweight and obesity among Chinese adults: a retrospective cross-sectional study from the China Health and Nutrition Survey. glob health res policy 7 , 41 Download citation. Received : 02 August Accepted : 19 October Published : 31 October Anyone you share the following link with will be able to read this content:. Pickett, K. an ecological study of obesity and income inequality. Health 59 , — Plurphanswat, N. BMC Obes. Pudney, S. Rahkonen, O. Public Health Policy 19 1 , 88— Tanumihardjo, S. Tjepkema, M. Health Rep. Wang, Y. Wardle, J. Public Health 92 8 , — Watson, B. De Politiques 42 2 , — WHO Obesity and overweight, obesity and overweight who. int Williams, R. Journal 6 1 , 58—82 Wurwarg J. Yongqing G. and Sun W. Zhou W. All theses Download references. The data set of this research is provided by the Turkish Statistical Institute. The authors thanks to Turkish Statistical Institute for granting permissions to use Income and Living Conditions Survey. The authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript. You can also search for this author in PubMed Google Scholar. All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by AMK and IŞS. The first draft of the manuscript was written by ŞAT and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work. Correspondence to Altuğ Murat Köktaş. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Reprints and permissions. Selçuk, I. Socioeconomic factors affecting the probability of obesity: evidence from a nationwide survey in Turkey. Qual Quant 57 , — Download citation. Accepted : 23 February Published : 09 March Issue Date : February Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Abstract Obesity, with its increasing incidence and prevalence, is a global and acute public health problem due to its high costs and strong negative relationship with many physical and mental health outcomes, including heart disease, diabetes, depression, and mortality. Access this article Log in via an institution. Data availability The data that support the findings of this study are available from Turkish Statistical Institute. References Alston, J. World Scientific Publishing Co, Singapore Google Scholar Andreyeva, T. Public Health 14 2 , 1—13 Article Google Scholar Bakhshi, E. Cambridge University Press Book Google Scholar European Commision: Ten key facts about nutrition and obesity-nutrition and obesity. European Commision, Brussels Google Scholar Cullinan, J. Lancet , — Article Google Scholar Dinsa, G. x Article Google Scholar Fang, H. Cambridge University Press, Cambridge Book Google Scholar Greene, W. Palgrave Macmillan, New York Google Scholar Hajizadeh, M. NCHS Data Brief , 1—8 Google Scholar Hojjat, T. Springer, Singapore Google Scholar Ipek, E. Cambridge, New York Book Google Scholar Maddala, G. Macmillian, New York Google Scholar Mann, R. Law 47 3 , — Google Scholar McElvey, R. Public Health Policy 19 1 , 88— Article Google Scholar Tanumihardjo, S. Public Health 92 8 , — Article Google Scholar Watson, B. De Politiques 42 2 , — Article Google Scholar WHO Obesity and overweight, obesity and overweight who. Journal 6 1 , 58—82 Google Scholar Wurwarg J. Acknowledgements The data set of this research is provided by the Turkish Statistical Institute. Funding The authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript. Author information Authors and Affiliations Bolu Abant İzzet Baysal University, Bolu, Turkey Işıl Şirin Selçuk Necmettin Erbakan University, Konya, Turkey Altuğ Murat Köktaş Tarsus University, Mersin, Turkey Şükrü Anıl Toygar Authors Işıl Şirin Selçuk View author publications. View author publications. Ethics declarations Conflict of Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Appendix 1 Appendix 1 See Table Table 6 Wald test results for parallel lines assumption using the. Rights and permissions Reprints and permissions. About this article. Cite this article Selçuk, I. Copy to clipboard. |
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Socioeconomic Factors Matter Low-intensity cycling workouts Health Research and Policy volume fqctorsArticle number: dactors Cite this article. Obsity details. With the rising prevalence of Socioeconomif and overweight, Obesity and socioeconomic factors number of Obesity and socioeconomic factors paid attention to the Heart health promotion tips effects socioeconomi human socikeconomic and life. Recent years, many studies have focused on the relation of socio-economic factors with the risk of overweight or obesity, but findings have been inconsistent. This study investigated the relationship between socio-economic factors and the risk of overweight and obesity among Chinese adults. This study was based on the survey of the China Health and Nutrition Survey inwith Chinese adults aged 18—65 years old. Overweight and obesity were assessed by physical measurements of weight, height, and waist circumference.
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