Social support for diabetes prevention -
We used the Social Support subscale of the Diabetes Care Profile DCP [ 29 ]. It includes twelve questions related to family and friend social support by adding up the six tangible support variables Follow meal plan, Take medicine, Take care of feet, Get activity, Test sugar and Handle feelings and the six emotional support variables Accept me, Feels uncomfortable, Encourage me, Discourage me, Listen to me, Nag me.
The level of social support was assessed using a five-point Likert scale strongly Disagree, Disagree, Neutral, Agree or Strongly Agree.
For the positively worded variable, a score of Agree or Strongly Agree was coded as 1 and that of Strongly Disagree, Disagree, Neutral was coded as 0. For the negatively worded variable, the reverse coding applied.
The raw scores ranged from 0 to To simplify interpretation of the scoring, the scores were transformed to a score ranging from 0 to , i. A higher score meant greater social support. A review of clinic notes to record the HbA1c readings of the last three clinic visits was conducted to assess glycaemic control on patients who had completed the questionnaire.
An overall HbA1c level was calculated as the average of the three separate readings. The interval between the readings varied for each participant, dependent on the appointment schedule.
Glycaemia control was considered good, acceptable or poor when the HbA1c level was lower than 7. Six fieldworkers were responsible for data collection using questionnaires and a review of medical records for HbA1c and blood glucose results, at the diabetic clinics in the four community health centres.
They were trained in the administration of data collection tools, research ethics and an approach to interviewing older persons. Patients with diabetes aged 60 years and over attending the four clinics on the date of data collection were approached for participation in the study. The study was conducted from April to October Questionnaires were completed for those who agreed to participate.
Signed consent to participate in the study was obtained before administration of the study questionnaire. The number of those who refused to participate in the study was not recorded. The fieldworkers were closely supervised by the research team to guarantee the quality of data collection.
A random sample of ten questionnaires was checked for completeness and correctness. A total of questionnaires were completed but seven were excluded from the analysis as the participants were below the age of 60 years. Data was managed and analysed using SPSS Statistics version 23, [ 31 ] and Stata Categorical data was summarised as frequency and proportions, and continuous data as mean and standard deviation SD.
Unpaired t-tests and one-way analysis of variance ANOVA were used to compare knowledge, self-management practice and social support scores between two and three or more group variables respectively. Ordinal logistic regression was used to determine associations between outcomes knowledge, self-management practice with components of social support scale.
Multivariable linear regression was used to evaluate the associations between outcomes knowledge, self-management practice and sociodemographic variables, glycaemia control, and social support S3 and S4 Tables.
Socio-demographic and clinical characteristics of the study sample are presented in Table 1. Two hundred thirty-three The majority were taking medication for other conditions: The HbA1c was higher than 8. Overall the level of knowledge was poor in The deficiencies were particularly noticeable in relation to symptoms of diabetes and complications of diabetes and hypertension.
There was a better level of knowledge about aspects of self-management e. Similarly, Over three-quarters of participants The majority of participants agreed that their family supported them to follow all aspects of self-care included in the questionnaire and encouraged them in managing their diabetes.
Only 74 The mean diabetes knowledge, self-management practice and social support scores of the participants by socio-demographic and clinical characteristics are presented in S1 and S2 Tables. The mean knowledge score was significantly lower for a single The social support score means also differed significantly with living arrangements; it was lowest in those living with a spouse On the other hand, there were no significant associations between diabetic knowledge, self-management practice and social support score with duration of diabetes, the type of medication used to treat diabetes, or receiving treatment for hypertension.
The ordinal logistic regression models of knowledge, self-management practice and the components of social support scale are given in Table 5.
The table shows the effect of the K and SMP indices on the 12 individual SS components, which were measured on a Likert scale. Multivariable linear regression analysis S3 and S4 Tables showed older age was negatively associated with knowledge ® : There were no significant associations between socio-demographic variables, HbA1c and social support with knowledge or self-management practice.
In this study, half of the participants had poor knowledge about diabetes and its complications. Just under two-thirds were assessed as having a good level of physical exercise and two-third of the participants were following a diabetic eating plan.
Three quarters perceived that their family supported them to follow all aspects of self-care management. Being in the high-income group was associated with good level of self-management practice. Finally, social support was positively associated with both knowledge and a number of self-care aspects.
The deficiencies noted in the participant's knowledge relating to the complications of diabetes and hypertension are alarming. Education of patients including those with diabetes is essential for self-management. It suggests in this study that whatever diabetes educational opportunities participants, particularly the older group, have been exposed to, have not been effective.
There are many potential reasons for this. For instance, the high patient numbers and multiple disease burden in primary care clinics, are likely to negatively impact on the time available for patient education by health promoters, nurses or doctors [ 32 ].
Other factors to be taken into consideration include lack of attendance at educational sessions when they take place, communication barriers, such as poor hearing, lack of concentration, inability to engage with the material presented and use of didactic modes of communication [ 33 ].
However, the participants seemed to have a better knowledge of self-management practice such as foot care and healthy eating. Whether this is because these messages are practical and easier to convey or that the information comes from multiple sources and not only health care workers is uncertain.
To date, there is a scarcity of evidence regarding diabetes self-management education and support in older adults [ 34 ]. For example, The Diabetes Education and Self-Management Ongoing and Newly Diagnosed DESMOND educators observed that older persons contributed to the group and brought valuable experience, but that they may have required a different approach at times [ 36 ].
However, no specific examples of such approaches were given in their study. Sinclair et al. reported that older people benefitted more than middle-aged people from a highly structured group diabetes self-management education intervention with embedded cognitive behavioural strategies compared to standard group education or individual sessions with dietitians and nurse educators [ 37 ].
As older persons may have difficulties concentrating and understanding abstract concepts, there is a need for educational material to be provided in the form of simple messages, delivered in a style that engages the person with diabetes and is personalized to their needs, with the emphasis on what they need to know, rather than all there is to know about diabetes [ 38 , 39 ].
Notably, these concepts to enhance knowledge and self-management practices are not unique to the older person with diabetes and are relevant in all societies.
Income and financial issues are possible barriers to optimum self-management for many older diabetic patients because of the costs of blood glucose testing, medication and following diet recommendations [ 39 ]. Earlier studies have shown that social support and social networks influence health behaviours and health outcomes [ 40 — 41 ].
For example, a study of family behaviours and relationships to adherence and metabolic control, individuals with diabetes negative perceptions of support from family were associated with lower adherence to diabetes management areas i.
glucose testing, diet adherence, and insulin injections. For instance, Sinclair et al. found that adherence to self-care regimens i. insulin treatments, monitoring blood glucose, exercise, and self-care away from home was associated with emotional and instrumental support from friends and family [ 42 ].
This suggests that the perceived availability and knowledge of friends and family as being present positively impacts self-management efforts of individuals with diabetes.
Furthermore, Connell et al found that social support had only a positive association with general morale among women, while there was a direct correlation between social support and adherence to treatment among older men with diabetes [ 43 ].
Among older persons, it has been found that women tend to exhibit better self-care behaviour, are less likely to be married, and are more likely to discuss personal issues with friends than men are [ 43 ]. This is in line with our study that showed that women tested their glucose levels more frequently than men.
In contrast, men are more likely to have a family member who assists with various aspects of their self-care regimen. The self-care behaviour of older women with diabetes is also influenced by social role obligations, and this is especially true of certain communities like the South African community, where women often bear a bigger responsibility as the caregiver for the whole family [ 43 ].
Unsurprisingly, such women also report a lower quality of life as well as encountering more barriers to the self-management of their diabetes [ 43 ]. Weaver et. al reported that both symptoms of diabetes and difficulties achieving socially important roles contribute to poor mental health among Indian diabetic women.
It is important to be aware of current DSME guidelines for older persons and how these guidelines can be implemented in a clinical setting.
However, older persons are under-represented in DSME research studies, so evidence-based guidelines specifically targeted toward older individuals are challenging to formulate [ 45 ].
The American Association of Diabetes Educators AADE and the American Geriatric Society AGS have formulated guidelines for DSME in the older adults mainly based on expert consensus [ 46 , 47 ].
For example, Older persons who are experiencing difficulties with daily tasks such as hearing loss, vision problems, decreased mobility and falls, will need individual rather than group DSME.
If needed, family members or other caregivers should be included in DSME [ 47 ]. Additional information about the influence of social support on chronic illness self-management has been supported by research. A systematic review reported evidence for a modest positive relationship between social support and chronic illness self-management, particularly for diabetes [ 48 ].
The finding was that a large information network is beneficial for self-management capabilities, especially in low education populations. This may be of an advantage in many cultures such as in South Africa where strong family relationships and family caring are important and highly valued [ 49 — 51 ].
A cohesive and supportive family may provide older diabetic patients with an opportunity to express feelings and fears. When DSMP is reviewed as a shared responsibility with the whole family, older persons may adopt DSMP activities more easily and feel more self-confident in managing diabetes [ 52 ].
As family-focused interventions may be more effective in improving DSMP performance than individual-focused interventions, including family members or friends in education programmes should be considered [ 53 — 56 ]. However, the shortage of professional health care workers in South Africa highlights the need to develop alternative delivery models for education and self-management for people with diabetes who attend primary care services.
These include using the services of community health workers CHWs and peer supporters and should draw on previous lessons learnt [ 56 ]. These included, finding suitable space for group education, with patient attendance and with full adoption of a guiding style by the health promoters.
Thus, groups held outside of primary care clinics in the community and led by well-trained CHWs or peers may be a better option, so too may the active participation by family members in these groups [ 57 ].
In addition, the emphasis on diabetes prevention programs in middle-aged people must be highlighted, because it will enable the next generation of older persons to live with a reduced diabetes burden.
For these reasons, South Africa's health care system needs to transform its services offered to older persons to reduce health care costs and ensure quality of life [ 57 ].
The various initiatives currently underway to re-engineer the primary healthcare system in SA to more effectively deal with NCDs, will go some way to meeting the identified needs of older diabetic patients and to addressing their barriers to care [ 58 — 60 ].
However, as part of this re-modelling exercise, it is perhaps opportune for the health department to consult older chronic care patients and involve them in decision making and the planning of services. This study alerts policymakers and clinicians to some of the specific issues considered to be pertinent and important in the care and management of older persons with diabetes.
As our results show that weak social support is a predictor of both poor knowledge and poor SMP, consideration should be given to health practitioners assessing social support when people with diabetes are reviewed clinically.
However, interventions need to be put in place to enhance the level of support. This could include recommending that the person be open to accepting support from family and friends, suggest that the main carer attend some clinic visits with the person or referral of the person to a support group.
This study contributes to an understanding and fills a gap in the current knowledge, relating to diabetes self-management practices, and perceived social support from family and friends and diabetes care for older people in South Africa. However, the study has some limitations.
First, as a cross-sectional survey design, our study could not assess cause and effect. Second, the measurements of self-report rather than direct observation of self-care practices are recognised as a limitation.
In addition, the use of a convenience sample drawn from a population who attend a diabetes clinic excludes those who did not attend. Fourth, our study was limited to one region and may not be representative of all older South Africans with diabetes.
Lastly, as an assessment tool, we have used a diabetes-related social support scale which we believe was a more specific tool in identifying diabetes specific social support than a more general social support scale.
However, it would have been strengthened by adding an open-ended component following the social support scale, for example asking the participant to list the top 3 ways that family and friends help in managing diabetes, and the 3 ways they help least in diabetes management.
Consideration needs to be given to developing and evaluating education programmes that focus on the needs of older people with diabetes mellitus and emphases the role of family and friends.
However, it is imperative to introduce programmes at a younger age so that diabetes self-management strategies are embedded as a life course perspective to enhance positive outcomes for persons living with diabetes.
The authors acknowledge the Chronic Diseases Initiative for Africa CDIA administrative Team, all field assistants, and the study participants, who provided useful information for this study. They gratefully acknowledge support Ms. Susan Terblanche from OLRAC SPS south Africa, Tawanda Chavies, Wisdom Basera from the Department of Medicine UCT who provided technical support and assisted in the data management.
Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Article Authors Metrics Comments Media Coverage Reader Comments Figures. Objective To determine the relationship of social support, especially that of family and friends with their self-management.
Methods This cross-sectional study was undertaken in the Cape Town metropole primary care clinics. Results Of the participants, Conclusions Consideration needs to be given to developing and testing education programmes that focus on needs of older people with diabetes and emphases the role of family and friends.
Shiyanbola, University of Wisconsin Madison School of Pharmacy, UNITED STATES Received: April 3, ; Accepted: February 24, ; Published: March 13, Copyright: © Werfalli et al. Fund Number: , Cost Centre: MEN Competing interests: The authors have declared that no competing interests exist.
Explanatory factors are closer proximity of underserved neighborhoods to nearby pollution sources, poor enforcement of regulations, and inadequate response to community complaints — Both food packaging and fast-food consumption, which can be high in low-income neighborhoods, can expose people to chemicals known to be endocrine disrupters — Examples include chemicals released from plastic packaging during microwave heating , higher urinary phthalate levels associated with fast food , and higher urinary bisphenol A levels from canned foods Certain personal care and cosmetic products, which are a source of phthalates and metals e.
In , the National Toxicology Program at the National Institute of Environmental Health Sciences convened an international workshop to evaluate the experimental and epidemiologic evidence on the relationship of environmental chemicals with obesity, diabetes, and metabolic syndrome — Evidence was deemed strongest for arsenic, with relative risks of diabetes found to range from 1.
More recent systematic reviews and meta-analyses present the growing literature examining multiple groups of chemicals , or specific groups of chemicals — Overall, the evidence supports an increased risk of diabetes in populations exposed to environmental chemicals including arsenic, persistent organic pollutants, phthalates, and possibly bisphenol.
Other reviews have reached conclusions consistent with this increased diabetes risk finding — The epidemiologic evidence is also supported by animal experiments showing that air pollution exposure can increase susceptibility to insulin resistance and T2DM — These findings highlight that populations more exposed to air pollution are also disproportionately at risk for developing diabetes.
There is epidemiologic and experimental evidence that environmental exposures increase susceptibility to cardiovascular disease CVD in people with diabetes. The evidence is extensive for air pollution exposures , Short-term increases in air pollution exposure are also related to higher risk of stroke mortality in patients with diabetes compared with those without In an experimental model, mice with diabetes exposed to diesel exhaust particles showed increased cardiovascular susceptibility compared with mice without diabetes In natural experiments in human populations, air pollution exposure also resulted in increased vascular reactivity and inflammation in patients with diabetes compared with those without In addition to air pollution, some evidence is also available for metals.
In the Strong Heart Study of American Indian adults followed since —, the risk of CVD associated with higher exposure to arsenic and cadmium was higher among participants with diabetes compared with those without diabetes , In a clinical trial in patients with a previous myocardial infarction Trial to Assess Chelation Therapy [TACT] , the beneficial effects of repeated chelation with disodium edetate on cardiovascular outcomes were greater in patients with diabetes Few studies have evaluated the effect of population-based or clinical interventions related to environmental exposures and diabetes prevention or control.
The increased risk of diabetes in populations exposed to environmental chemicals and the increased susceptibility for diabetes complications in individuals with diabetes exposed to air pollution potentially provides an opportunity for prevention and treatment that can be particularly relevant for the most vulnerable populations.
Because individuals generally have limited control over environmental agents, the most effective interventions will be at the population level, through policy and regulation, with a particular focus on protecting marginalized and underserved populations.
There is evidence that declines in air pollution levels and metal exposures have contributed to improvements in CVD development , ; benefits for diabetes development are pending. Research is also needed to test intermediate strategies at the clinical level, such as exposure screening e.
It is also referred to as the community food environment e. Key dimensions of the food environment include accessibility, availability, affordability, and quality — These factors, which define the quality of the food environment, are of particular importance in marginalized communities, which may have poor access to supermarkets and healthy foods but abundant access to fast-food outlets and energy-dense foods and are often disproportionately impacted by physical hazards e.
At their root, differences in the food environment can be caused by government policies and incentives, and the legacy of such policies as redlining and segregation. Cross-sectional studies have shown associations between food access, availability, geographic characteristics, and T2DM prevalence.
Ahern et al. for food access assessed as percent of households with no car living more than one mile from a grocery store and food availability assessed as number of fast-food restaurants, full-service restaurants, grocery stores, convenience stores, and per capita sales in dollars from local farms made directly to consumers.
Higher access to food was associated with lower T2DM rates in metro and nonmetro counties, and higher availability of full-service restaurants and grocery stores and lower availability of fast-food and convenience stores were associated with lower diabetes rates Haynes-Maslow and Leone similarly found availability of full-service restaurants to be associated with lower prevalence of diabetes in adults and availability of fast-food restaurants generally to be associated with higher diabetes prevalence.
Several observational, longitudinal studies report neighborhood resources in general, and access and availability of the food environment in particular, as associated with diabetes prevalence and incidence A systematic review by den Braver et al.
Heterogeneity across the studies prevented the conduct of meta-analyses. Gabreab et al. In a longitudinal employee cohort, Herrick et al. Christine et al. Studies have also examined both food and PA environments in combination and diabetes risk.
Meyer et al. In lower—population density areas, higher food and PA resource diversity relative to other clusters was significantly associated with higher diet quality Neighborhood clusters were inconsistently associated with BMI or insulin resistance and not associated with fast-food consumption, or walking, biking, or running Tabaei et al.
Individuals who lived continuously in the most advantaged residential areas, including greater ratio of healthy food outlets to unhealthy food outlets and residential walkability, achieved increased glycemic control and took less time to achieve glycemic control compared with the individuals who lived continuously in the least advantaged residential areas Kern et al.
In a longitudinal study, they examined food affordability and neighborhood price of healthier food relative to unhealthy food and its association with T2DM and insulin resistance.
Higher prices of healthy foods relative to unhealthy foods were found to be associated with lower odds of having a high-quality diet; however, there was no association with diabetes incidence or prevalence More studies are needed in this area.
Food insecurity is defined as not having adequate quantity and quality of food at all times for all household members to have an active, healthy life , Researchers have investigated several pathways through which food insecurity may worsen T2DM outcomes — First, in the nutritional pathway , food insecurity is associated with lower diet quality , which is in turn associated with higher HbA 1c.
Food insecurity incentivizes more affordable, energy-dense foods that can directly raise serum glucose e. and may lead to greater insulin resistance , Conversely, low or inconsistent food availability can increase risk of hypoglycemia.
Second, via a compensatory pathway , behavioral strategies necessary to cope with the immediate problem of food insecurity can inadvertently undermine T2DM management. For example, financial resources that might otherwise have been used for medications or diabetes care supplies are diverted to meet dietary needs , — Several studies have reported a relationship between food insecurity and adverse diabetes outcomes , , and a review by Barnard et al.
Three studies reported food bank and pantry interventions with food insecure clients with T2DM , , Seligman et al. The study resulted in improvements in HbA 1c , fruit and vegetable consumption, self-efficacy, and medication adherence.
In a randomized controlled trial of the intervention, Seligman et al. Palar et al. Studies have examined effect of supermarket gain or loss on T2DM outcomes. Results over 4 years of tracking supermarket change in low-income neighborhoods showed that relative to no change in supermarket presence, supermarket loss was associated with worse HbA 1c trajectories, especially among those with highest HbA 1c.
Supermarket gain in neighborhoods was associated with marginally better HbA 1c outcomes, but only for those with near-normal HbA 1c baseline values Results for the intervention neighborhood receiving the supermarket showed improved perceived access to healthy food , and the prevalence of diabetes increased less in the neighborhood with the supermarket than in the comparison neighborhood.
Since the initiation of the supermarket, many other investments including greenspace, housing, and commercial spaces have been implemented in the intervention neighborhood Results of these neighborhood investments on measured BMI, blood pressure, HbA 1c , and HDL cholesterol will be forthcoming.
In sum, food environment factors of food unavailability, inaccessibility, and insecurity each demonstrate associations with worse diabetes risk and outcomes, and interventions including diabetes-targeted food and self-management care at food banks and pantries and increasing grocery store presence in low-income neighborhoods are few, but collectively they demonstrate the potential to impact diabetes risk, clinical outcomes, and psychosocial outcomes.
Health care as a SDOH includes access, affordability, and quality of care factors. In population-based studies, having health insurance is the strongest predictor of whether adults with diabetes have access to diabetes screenings and care Uninsured adults in the U.
population have a higher likelihood of having undiagnosed diabetes than adults with insurance Liese et al. Having insurance has also been found to attenuate associations of financial barriers with higher HbA 1c Geographic access to adult and pediatric endocrinologists varies substantially by state and county in the U.
S , with disparities in access in many of the geographic regions with highest diabetes prevalence and socioeconomic disadvantage , Similarly, factors that increase odds of having a diabetes self-management education program in a geographic area include a higher percentage of the population with at least a high school education, a higher percentage of insured individuals, and a lower rate of unemployment DeVoe et al.
Being uninsured and without a usual source of care was associated with three to five times lower odds of adults receiving an HbA 1c screen, blood pressure check, or access to urgent care when needed Among adolescents and young adults with diabetes who had state or federal health insurance, not having any usual source of provider primary care or diabetes specialist was associated with higher HbA 1c than having a usual source of provider, and HbA 1c was similar whether in primary care or specialist care On average, health care costs of people with diabetes are 2.
Cost-related or cost-reducing nonadherence CRN is associated with income, insured status, and type of insurance.
Within a diabetes clinic population of adults with T1DM or T2DM prescribed insulin, odds of CRN were three times higher for those with Medicaid or no insurance compared with those with Medicare Piette et al.
Compared with VA patients with diabetes, risk of CRN was found to be almost three times higher for privately insured patients and four to eight times higher for patients with Medicare, Medicaid, or no health insurance Higher financial stress, financial insecurity, and financial barriers are associated with likelihood of CRN , People with CRN experience poorer diabetes management, higher HbA 1c , and decreased functional status , Deaths have been reported from insulin CRN among youth and adults with T1DM Having insurance is the strongest single predictor of whether adults with diabetes are likely to meet individual quality measures of diabetes care Sociodemographic disparities in care quality are well documented in national reports and recommendations 2 and appear to remain consistent over time population-based study of achievement of a composite diabetes treatment goal from to , data from to showed that non-Hispanic Blacks had lower odds of achieving a composite diabetes quality measure than non-Hispanic Whites adjusted OR 0.
Within insured settings, disparities have been reported among Blacks as compared with Whites—in measures including dilated eye exam taken; LDL test taken; LDL, blood pressure, or HbA 1c control; and statin therapy — A study of 21 VA facilities found Blacks with diabetes were more likely than Whites with diabetes to receive care at lower-performing facilities overall, which explained some racial differences in diabetes quality measures Several systematic reviews have concluded that community health worker CHW interventions using trained lay workforces are effective for multiple outcomes in underserved African American and Hispanic adults with T2DM and comorbid conditions — CHWs have been integrated into care delivery , with reimbursement in some states Roles of CHWs include patient navigation, appointment scheduling, visit attendance, patient education, home-based monitoring, assessment of social needs and connection with social services, social support, and advocacy , Reported outcomes include better diabetes knowledge and self-care behaviors, increased quality of life, reduced emergency visits and hospitalizations, reduced costs, and modest improvements in glycemic control — , , using home-based or integrated health team delivery models , A majority of the CHW interventions designed for adult populations with diabetes have been diabetes-focused in content and goals and have utilized structured curricula ; however, one series of studies reported use of a standardized, all-condition CHW intervention and found modest gain in diabetes outcomes along with additional health benefits , There is also evidence of effectiveness of self-management interventions delivered directly to underserved patients with diabetes when interventions are designed to overcome barriers.
In a series of studies, a problem-based self-management training addressing multiple life barriers to care in low-income and minority populations was adapted for low literacy and prevalent diabetes-related functional limitations e. Studies have examined the impact of the Affordable Care Act ACA on insurance coverage and health care access for patients with diabetes Among people with diabetes in the lowest income strata, the proportion of income spent on health costs decreased significantly from 6.
Other studies found increased access to care, diabetes management, and health status among people with diabetes in Medicaid expansion states as compared with their counterparts in non—Medicaid expansion states ; increased rates of diabetes detection and diagnosis among Medicaid patients with undiagnosed diabetes in states with Medicaid expansion ; and reduction in cost-related medication nonadherence rates and uninsured rates among people with diabetes following ACA Several multidimensional factors shape the social environment as a determinant of health , including social capital, social cohesion, and social support 28 , Social capital is defined as the features of social structures that serve as resources for collective action e.
Bonding social capital refers to trusting and co-operative relations between members of a network who see themselves as being similar in terms of their shared social identity; by contrast, bridging social capital refers to aspects of respect and mutuality between people who do not share social identities e.
Racism, discrimination, and inclusion versus exclusion are macro-level social capital factors that impact health Social cohesion refers to the extent of connectedness and solidarity among groups in a community , and has two dimensions: reduction of inequalities and patterns of social exclusion of population subgroups from full participation in society and strengthening of social relationships and interactions — Social cohesion actions facilitate the goal of keeping the society united, not only through social relations, community ties, and intergroup harmony but also through reducing bias and discrimination toward economically disadvantaged groups within a society, such as women and ethnic minorities Categories include emotional support, tangible support, informational support, and companionship — Social support is theorized to operate by either buffering the effects of poor health or by directly impacting health , A systematic review by Flôr et al.
However, the few studies available and variations among populations and measures limit the ability to draw firm conclusions related to dimensions of social capital and whether the association is the same at the individual or neighborhood level , — Gebreab et al.
Studies demonstrating the relationship between social support and diabetes have associated increased social support with better glycemic control and improved quality of life — , while lack of social support has been associated with increased mortality and diabetes-related complications A number of studies suggest social cohesion, social capital, and social support may influence—or be influenced by—racism and discrimination Racism interacts with other social entities, creating a set of dynamic, interdependent components that reinforce each other, sustaining racial inequities and promoting both institutional- and individual-level discrimination across various sectors of society impacting diabetes incidence , For example, Whitaker et al.
Further work is needed to understand the multiple ways that the social environment influences inequities in diabetes outcomes. To our knowledge, there is no empirical research on social capital or social cohesion interventions and impact on diabetes outcomes, but a body of literature has examined effects of social support.
The systematic review by Strom and Egede of 18 observational studies of adults with T2DM found that higher levels of social support were associated with outcomes including better glycemic control, knowledge, treatment adherence, quality of life, diagnosis awareness and acceptance, and stress reduction Lack of social support has been linked with increased mortality and diabetes-related complications in T2DM , With regard to preferences—in a study conducted before the coronavirus disease pandemic—Sarkar et al.
Reliance on support from family and community tended to be higher in minority populations, while Whites relied more on media and health care professionals International and U.
national committees have convened to provide guidance on SDOH intervention approaches. These expert committee recommendations are not specific to any disease; rather, they are applicable to all conditions and populations of health inequity. Table 3 displays recommendations from the WHO Commission on Social Determinants of Health 27 , the National Academies of Sciences, Engineering, and Medicine NASEM formerly, Institute of Medicine Committee on the Recommended Social and Behavioral Domains and Measures for Electronic Health Records 80 , the NASEM Committee on Educating Health Professionals to Address the Social Determinants of Health , and the NASEM Committee on Integrating Social Needs Care into the Delivery of Health Care to Improve the Nation's Health 5.
The WHO recommendations are unique in their emphasis on root-cause, multisector interventions designed to remove the SDOH as a barrier to health equity. The NASEM recommendations are based in the health care sector and, collectively, focus on integration of SDOH into the health care mission, operations, and financial model.
Many health care systems are utilizing electronic medical records and health information exchanges to capture SDOH data and commercially available SDOH algorithms to identify patients at social risk and trigger service referrals NASEM provided assessment questions to capture SDOH domains and frequencies for assessment with evidence of feasibility Examples of resources on SDOH available for health care organizations and health care professionals.
There is SDOH evidence supporting associations of SES, neighborhood and physical environment, food environment, health care, and social context with diabetes-related outcomes.
Inequities in living and working conditions and the environments in which people reside have a direct impact on biological and behavioral outcomes associated with diabetes prevention and control 12 , Life-course exposure based on the length of time one spends living in resource-deprived environments—defined by poverty, lack of quality education, or lack of health care—significantly impacts disparities in diabetes risk, diagnosis, and outcomes 12 , 48 , Although the review reports SDOH intervention studies for aspects of housing, built and food environment, and health care, there appears to be relatively limited U.
A clinical context alone, however, is too narrow to accommodate systemic SDOH influences. Structural and legal interventions are needed to address root causes driving SDOH 27 , Similarly, additional emphasis is needed on a next generation of research that prioritizes interventions impacting the root causes of diabetes inequities, rather than compensatory interventions assisting the individual to adapt to inequities 18 , For example, in the U.
antiliteracy laws for Blacks, which prohibited Blacks from being taught to read or write, persisted until the s in some states , , and laws prohibiting African Americans from attending public and private schools Whites attended continued until and , respectively Although adapting health materials for low-literacy suitability is an effective intervention to compensate for centuries of legal racial discrimination in educational access and quality, a next-generation intervention might target the education sector and implement delivery of high-quality early education to all within both the public and private school systems and with equitable educational funding for sociodemographic populations.
Similarly, while partnerships to bring bags of healthy groceries to low-income families living in food deserts are important to compensate for food deserts, a next-generation approach might target historical redlining and zoning policies that are the root cause of absence of supermarkets and fresh food markets in minority and lower-income neighborhoods — The review has limitations.
First, the undertaking was designed to summarize literature on the range of SDOH identified as having impact on diabetes outcomes.
As such, this article describes findings from systematic reviews and meta-analyses as well as more recent published studies on the named SDOH; it was not designed as a primary systematic review of all published research on the topic.
Second are limitations of the research itself, including wide variability in measures and definitions used in studies within an SDOH area, making it more difficult to describe outcomes for an SDOH area in a consistent or uniform manner or to report quantitative outcomes derived from meta-analyses.
Third, this review was U. Finally, the many complexities of SDOH and their potentially different pathways and impacts on populations are beyond the scope of this initial review and require attention to specificity in designs of future SDOH research in diabetes. Recommendations for SDOH research in diabetes resulting from this SDOH review are described in Table 5 and include establishing consensus SDOH definitions and metrics, designing studies to examine specificities based on populations, prioritizing next-generation interventions, embedding SDOH context within dissemination and implementation science in diabetes, and training researchers in methodological techniques for future SDOH intervention studies.
By addressing these critical elements, there is potential for progress to be realized in achieving greater health equity in diabetes and across health outcomes that are socially determined. See accompanying articles, pp.
The authors express appreciation to Malaika I. Hill and Mindy Saraco of the American Diabetes Association; Elizabeth A.
Vrany, Johns Hopkins University School of Medicine; and Shelly Johnson, Washington University in St. Louis, for providing technical assistance for this review. is supported in part by the Johns Hopkins Institute for Clinical and Translational Research ICTR , which is funded in part by grant UL1TR from the National Center for Advancing Translational Sciences NCATS , a component of the National Institutes of Health NIH and NIH Roadmap for Medical Research.
is also supported in part by NIH National Heart, Lung, and Blood Institute NHLBI grant T32HL is supported in part by NIH National Institute of Diabetes and Digestive and Kidney Diseases NIDDK grant P30DK is supported in part by NIH and NIDDK grant P30DK is supported in part by NHLBI grant R01HL is supported in part by National Institute of Environmental Health Sciences grants P42ES and P30ES is supported in part by NIDDK grant K23DK The findings and conclusion in this report are those of the authors and do not necessarily represent the official position of the Johns Hopkins ICTR, NCATS, NIH, NIDDK, or any other institution mentioned in the article.
Duality of Interest. received personal fees for service on an advisory board about prioritizing food insecurity research topics for the Aspen Institute. No other potential conflicts of interests relevant to this article were reported.
Author Contributions. researched data and wrote the manuscript. researched data and contributed to writing the manuscript. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest.
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Definitions of Health Disparities, Health Equity, and SDOH. SDOH Nomenclatures and Contextual Factors. Review of SDOH and Diabetes. Linkages Across Health Care and Community Sectors to Address SDOH.
Article Information. Article Navigation. Scientific Review November 02 Social Determinants of Health and Diabetes: A Scientific Review Felicia Hill-Briggs ; Felicia Hill-Briggs. Corresponding author: Felicia Hill-Briggs, fbriggs3 jhmi. This Site. Google Scholar. Nancy E. Adler ; Nancy E. Seth A.
Berkowitz Marshall H. Chin ; Marshall H. Tiffany L. Gary-Webb ; Tiffany L. Ana Navas-Acien ; Ana Navas-Acien. Pamela L. Thornton ; Pamela L. Debra Haire-Joshu Debra Haire-Joshu. Louis, St. Louis, MO. Diabetes Care ;44 1 — Article history Received:. Connected Content. A commentary has been published: Social Determinants of Health and Structural Inequities—Root Causes of Diabetes Disparities.
A commentary has been published: A Lesson From Public Health Matters for Both COVID and Diabetes. A commentary has been published: Metabolic Syndrome and COVID Mortality Among Adult Black Patients in New Orleans.
Get Permissions. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Table 1 Definitions. Health disparities adversely affect groups of people who have systematically experienced greater obstacles to health based on their racial or ethnic group; religion; socioeconomic status; sex; age; mental health; cognitive, sensory, or physical disability; sexual orientation or gender identity; geographic location; or other characteristics historically linked to discrimination or exclusion Health equity Equity is the absence of avoidable, unfair, or remediable differences among groups of people, whether those groups are defined socially, economically, demographically, or geographically or by other means of stratification.
Health equity is attainment of the highest level of health for all people. Achieving health equity requires valuing everyone equally with focused and ongoing societal efforts to address avoidable inequalities, historical and contemporary injustices, and the elimination of health and health care disparities Social determinants of health SDOH The social determinants of health are the conditions in which people are born, grow, live, work, and age.
These circumstances are shaped by the distribution of money, power, and resources at global, national, and local levels. The social determinants of health are mostly responsible for health inequities—the unfair and avoidable differences in health status seen within and between countries View Large.
Figure 1. View large Download slide. Table 2 SDOH and component factors included in the diabetes review. Socioeconomic status. Neighborhood and physical environment. Food environment. Health care. Social context. Education Housing Food security Access Social cohesion Social capital Social support Income Built environment Food access Affordability Quality Occupation Toxic environmental exposures Food availability.
Table 3 SDOH intervention recommendations from international and national U. Recommended actions. Commission on the Social Determinants of Health, WHO 27 Improve daily living conditions Put major emphasis on early childhood education and development.
Improve living and working conditions. Create social protection policy supportive of all. Tackle the inequitable distribution of power, money, and resources Create a strong public sector that is committed, capable, and adequately financed.
Ensure legitimacy, space, and support for civil society, for an accountable private sector, and for the public to agree to reinvestment in collective action. Measure and understand the problem and assess the impact of action Acknowledge there is a problem.
Ensure that health inequity is measured. Develop national and global health equity surveillance systems for routine monitoring of health inequity and the social determinants of health.
Evaluate the health equity impact of policy and action. Ensure stronger focus on social determinants in public health research. Prepare health professionals to take action on SDOH To prepare health professionals to take action on the social determinants of health in, with, and across communities, health professional and educational associations and organizations at the global, regional, and national levels should apply [frameworks for] partnering with communities to increase the inclusivity and diversity of the health professional student body and faculty.
Integrate SDOH into organizational mission and values Governments and individual ministries e. Build the evidence base for SDOH learning, intervention, and evaluation approaches Governments, health professional and educational associations and organizations, and community organizations should use [a social determinants] framework and model to guide and support evaluation research aimed at identifying and illustrating effective approaches for learning about the social determinants of health in and with communities while improving health outcomes, thereby building the evidence base.
Committee on Integrating Social Needs Care Into the Delivery of Health Care to Improve the Nation's Health, NASEM 5 Design health care delivery to integrate social care into health care, guided by the five health care system activities—awareness, adjustment, assistance, alignment, and advocacy Establish organizational commitment to addressing disparities and health-related social needs.
Incorporate strategies for screening and assessing for social risk factors and needs. Incorporate social risk into care decisions using patient-centered care. Establish linkages between health care and social service providers.
Include social care workers in team care. Develop infrastructure for care integration, including financing of referral relationships with select social providers. Build a workforce to integrate social care into health care delivery Social workers and other social care workforces should be providers eligible for reimbursement from payers.
Integrate SDOH competencies in medical and health professional credentialing. Develop a digital infrastructure that is interoperable between health care and social care organizations Establish ACA-recommended digital infrastructure for social care. The Office of the National Coordinator should support identification of interoperable, secure, platforms for use across health and social care communities.
The Federal Health Information Technology Coordinating Committee should facilitate data sharing across domains e. Analytic and technology implementation must have an explicit focus on equity to avoid unintended consequences such as perpetuation or aggravation of discrimination, bias, and marginalization.
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Socioeconomic position, type 2 diabetes and long-term risk of death. PloS One. Pandit AU , Bailey SC , Curtis LM , et al. Disease-related distress, self-care and clinical outcomes among low-income patients with diabetes. J Epidemiol Community Health. Strom JL , Egede LE. The impact of social support on outcomes in adult patients with type 2 diabetes: a systematic review.
Curr Diab Rep. Nicolucci A , Kovacs Burns K , Holt RIG , et al. Diabetes Attitudes, Wishes and Needs second study DAWN2TM : cross-national benchmarking of diabetes-related psychosocial outcomes for people with diabetes.
Kovacs Burns K , Nicolucci A , Holt RIG , et al. Diabetes Attitudes, Wishes and Needs second study DAWN2TM : cross-national benchmarking indicators for family members living with people with diabetes. Holt RIG , Nicolucci A , Kovacs Burns K , et al.
Diabetes Attitudes, Wishes and Needs second study DAWN2TM : cross-national comparisons on barriers and resources for optimal care--healthcare professional perspective. Rosland AM , Heisler M , Choi HJ , Silveira MJ , Piette JD. Family influences on self-management among functionally independent adults with diabetes or heart failure: do family members hinder as much as they help?
Chronic Illn. Rintala TM , Jaatinen P , Paavilainen E , Astedt-Kurki P. Interrelation between adult persons with diabetes and their family: a systematic review of the literature.
J Fam Nurs. Reddy J , Wilhelm K , Campbell L. Putting PAID to diabetes-related distress: the potential utility of the problem areas in diabetes PAID scale in patients with diabetes.
Polonsky WH , Anderson BJ , Lohrer PA , et al. Assessment of diabetes-related distress. Zimet GD , Powell SS , Farley GK , Werkman S , Berkoff KA. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess. Zimet GD , Dahlem NW , Zimet SG , Farley GK.
The Multidimensional Scale of Perceived Social Support. Glasheen WP , Renda A , Dong Y. Diabetes Complications Severity Index DCSI -- Update and ICD translation. J Diabetes Complicat. Nam CB , Boyd M. Occupational status in over a century of census-based measurement. Popul Res Policy Rev.
Tables of Sample Size Requirement for Multiple Regression. Accessed on September 21, United States Census Bureau. Access on September 20, Hermanns N , Kulzer B , Krichbaum M , Kubiak T , Haak T.
How to screen for depression and emotional problems in patients with diabetes: comparison of screening characteristics of depression questionnaires, measurement of diabetes-specific emotional problems and standard clinical assessment.
Young-Hyman D , de Groot M , Hill-Briggs F , Gonzales JS , Hood K , Peyrot M. Holt-Lunstad J , Smith TB , Layton JB. Social relationships and mortality risk: a meta-analytic review. PLoS Med. Lee AA , Piette JD , Heisler M , Rosland A-M. Diabetes distress and glycemic control: the buffering effect of autonomy support from important family members and friends.
Search in Google Scholar PubMed PubMed Central. Rosland AM , Kieffer E , Israel B , et al. When is social support important? The association of family support and professional support with specific diabetes self-management behaviors. J Gen Intern Med. Ozcan B , Rutters F , Snoek FJ , et al. High diabetes distress among ethnic minorities is not explained by metabolic, cardiovascular, or lifestyle factors: findings from the Dutch Diabetes Pearl cohort.
Schmidt CB , Potter van Loon BJ , Torensma B , Snoek FJ , Honig A. Ethnic minorities with diabetes differ in depressive and anxiety symptoms and diabetes-distress.
J Diabetes Res. Seffinger MA , King HH , Ward RC , et al. Osteopathic philosophy. In: Chila AG , ed. Foundations of Osteopathic Medicine , 3rd ed. Your purchase has been completed. Your documents are now available to view. Publicly Available Published by De Gruyter October 8, From the journal Journal of Osteopathic Medicine.
Download article PDF. Cite this Share this. Abstract Context Diabetes is a complex, chronic condition and managing it can have psychosocial implications for patients, including an impact on relationships with their loved ones and physical wellness. Objective To investigate the association between diabetes-related distress and perceived social support among people with type 2 diabetes.
Methods This cross-sectional study surveyed a population with a lower socioeconomic status Medi-Cal recipients, which are only given to low-income individuals in Solano County, California.
Conclusion Our findings suggest that a higher level of perceived social support experienced was associated with lower diabetes-related distress among patients with type 2 diabetes.
For more information about PLOS Subject Support, click Low GI smoothies. Self-management preventiin challenging for diabetew those with suppot condition but Low GI smoothies likely to siabetes a higher demand for those who may Craving control solutions existing Boost energy for better sleep associated Boost energy for better sleep age, and long-standing chronic diseases. To determine the relationship of social support, especially that of family and friends with their self-management. This cross-sectional study was undertaken in the Cape Town metropole primary care clinics. The sample comprised people drawn from four community health centres CHC that are served by Groote Schuur Hospital at the tertiary level. Of the participants, The mean duration of diabetes from diagnosis was eight years.Ninfa Peña-Purcell. A supportive preventioh network can help older adults make and maintain necessary behavior changes to manage their diabetes. Inviting preevntion family member or friend to participate in a diabetes self-management education and support DSMES class can be a win-win. Remember suppport share the A.
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Interventions focused on coaching the family and friend supporters to activate older adults with diabetes are needed. Live in Controland its Spanish counterpart Vivir en Controlformerly ¡Sí, Yo Puedo Controlar Mí Diabetes! An emphasis of Live in Control is building good communication.
This program exemplifies a practical approach to equipping and educating a family member or friend in their role in supporting a loved one with diabetes. Providing ongoing social support to older adults with diabetes cannot be overlooked.
With help from others, older adults can be motivated and activated in their self-care practices. acronym, three simple tips for older adults with diabetes to seek support:.
Centers for Disease Control and Prevention. Prevalence of Both Diagnosed and Undiagnosed Diabetes. Buttorff C, Ruder T, Bauman M. Multiple Chronic Conditions in the United States. Found on the internet at www. Barnes MD, Hanson CL, Novilla LB, Magnusson BM, Crandall AC, Bradford G.
Family-Centered Health Promotion: Perspectives for Engaging Families and Achieving Better Health Outcomes. J Health Care Organ Provision Finan.
Dan Grabowski D, Reino MB, Andersen TH. Mutual Involvement in Families Living with Type 2 Diabetes: Using the Family Toolbox to Address Challenges Related to Knowledge, Communication, Support, Role Confusion, Everyday Practices and Mutual Worries. Kreider KE. Diabetes Distress or Major Depressive Disorder?
A Practical Approach to Diagnosing and Treating Psychological Comorbidities of Diabetes. Diabetes Ther. dOI Peña-Purcell N Cutchens L, McCoy T. J J Transcultural Nurs, doi American Diabetes Association.
Diabetes Care. Facilitating behavior change and well-being to improve health outcomes: Standards of Medical Care in Diabetes — Anjali M, Khapre M, Kant R, Asha TJ. How Well a Culturally Adapted Diabetes Self-Management Education Program DSME Improves the Glycemic Control and Distress Among Diabetes Patients?
J Cardio Diabetes Metab Disord. Rosland AM, Piette JD, Trived R, Kerr EA, Shelley Stoll S, Tremblay A, Heisler M. Engaging family supporters of adult patients with diabetes to improve clinical and patient-centered outcomes: study protocol for a randomized controlled trial.
This project was supported, in part by grant number 90CSSG from the U. Administration for Community Living, Department of Health and Human Services, Washington, D. Grantees undertaking projects under government sponsorship are encouraged to express freely their findings and conclusions.
Points of view or opinions do not, therefore, necessarily represent official Administration for Community Living policy. Get information on prevention and how to manage ongoing health conditions focused on physical and mental health. From exercise tips to diet and nutrition, this is your one-stop shop for caring for yourself and loved ones.
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Find us on Social. Diabetes for Older Adults Older Adults and Diabetes: How Social Support Can Help Jul 29, 6 min read.
Key Takeaways A supportive social network can help older adults make and maintain necessary behavior changes to manage their diabetes. How social connections help older adults manage diabetes Social connections can play an important role in helping older adults manage diabetes, especially when combined with other health concerns.
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: Social support for diabetes prevention| Help Prevent Type 2 Diabetes | Table 3 displays recommendations from the WHO ;revention on Social Determinants Boost energy for better sleep Health 27the National Slcial of Sciences, Uspport, and Medicine NASEM diaebtes, Institute of Medicine Committee on Social support for diabetes prevention Prevemtion Social and Behavioral Domains Antioxidant-Rich Holistic Remedies Measures for Electronic Health Records fiabetesthe NASEM Committee on Educating Health Professionals to Soxial the Social Herbal beauty supplement of Healthand the NASEM Committee on Integrating Social Needs Care into the Delivery of Health Care to Improve the Nation's Health 5. This social support framework seems to be useful for identifying the types of categories that are most relevant in different diseases. If the DSSQ-Family added significantly to the prediction of adherence, it would support the incremental and predictive validity of the DSSQ-Family and highlight the importance of family support for adolescents' diabetes care. Google Scholar Andersson T, Alfredsson L, Kallberg H, Zdravkovic S, Ahlbom A. Koetsenruijter J, van Lieshout J, Lionis C, Portillo MC, Vassilev I, Todorova E, Foss C, Gil MS, Knutsen IR, Angelaki A. DV: Treatment adherence Step 1: Adolescent age. |
| JMIR Diabetes - Social Support in a Diabetes Online Community: Mixed Methods Content Analysis | A knowledge, attitude and practice KAP study of diabetes mellitus among patients attending Klinik Kesihatan Seri Manjung. Louis, for providing technical assistance for this review. Procidano, M. Osteopathic Considerations for the Pregnant Patient With COVID Evaluation of the association between arsenic and diabetes: a National Toxicology Program workshop review. Health systems subject to community benefit regulations should comply with those regulations and should align their hospital licensing requirements and public reporting with community benefits regulations and should link their community benefits providing social care. Journal of Pediatric Psychology , 17 , |
| Key Takeaways | Differences by diabetes Social support for diabetes prevention Caffeine and muscle soreness less pronounced in men after adjustment for social diabbetes covariates but supprot significant step Social support for diabetes prevention. Moore AR, Prybutok V, Ta A, Amey F. Please login or register with De Gruyter to order this product. researched data and wrote the manuscript. The study by Aalto et al. Built environment and cardio-metabolic health: systematic review and meta-analysis of longitudinal studies. |
| Older Adults and Diabetes: How Social Support Can Help | An emphasis of Live in Control is building good communication. This program exemplifies a practical approach to equipping and educating a family member or friend in their role in supporting a loved one with diabetes. Providing ongoing social support to older adults with diabetes cannot be overlooked. With help from others, older adults can be motivated and activated in their self-care practices. acronym, three simple tips for older adults with diabetes to seek support:. Centers for Disease Control and Prevention. Prevalence of Both Diagnosed and Undiagnosed Diabetes. Buttorff C, Ruder T, Bauman M. Multiple Chronic Conditions in the United States. Found on the internet at www. Barnes MD, Hanson CL, Novilla LB, Magnusson BM, Crandall AC, Bradford G. Family-Centered Health Promotion: Perspectives for Engaging Families and Achieving Better Health Outcomes. J Health Care Organ Provision Finan. Dan Grabowski D, Reino MB, Andersen TH. Mutual Involvement in Families Living with Type 2 Diabetes: Using the Family Toolbox to Address Challenges Related to Knowledge, Communication, Support, Role Confusion, Everyday Practices and Mutual Worries. Kreider KE. Diabetes Distress or Major Depressive Disorder? A Practical Approach to Diagnosing and Treating Psychological Comorbidities of Diabetes. Diabetes Ther. dOI Peña-Purcell N Cutchens L, McCoy T. J J Transcultural Nurs, doi American Diabetes Association. Diabetes Care. Facilitating behavior change and well-being to improve health outcomes: Standards of Medical Care in Diabetes — Anjali M, Khapre M, Kant R, Asha TJ. How Well a Culturally Adapted Diabetes Self-Management Education Program DSME Improves the Glycemic Control and Distress Among Diabetes Patients? J Cardio Diabetes Metab Disord. Rosland AM, Piette JD, Trived R, Kerr EA, Shelley Stoll S, Tremblay A, Heisler M. Engaging family supporters of adult patients with diabetes to improve clinical and patient-centered outcomes: study protocol for a randomized controlled trial. This project was supported, in part by grant number 90CSSG from the U. Administration for Community Living, Department of Health and Human Services, Washington, D. Grantees undertaking projects under government sponsorship are encouraged to express freely their findings and conclusions. Points of view or opinions do not, therefore, necessarily represent official Administration for Community Living policy. Get information on prevention and how to manage ongoing health conditions focused on physical and mental health. From exercise tips to diet and nutrition, this is your one-stop shop for caring for yourself and loved ones. We use cookies to give you the best experience on our website. For more information on what this means and how we use your data, please see our Privacy Policy. Skip to Main Content. Adviser Age Well Planner About Us Ways to Give Get Involved A A. Older Adults Find Content COVID Health Falls Prevention Medicare Money Age Well Planner. Professionals Find Content Center for Benefits Access Center for Healthy Aging National Institute of Senior Centers Aging Mastery®. Back to Main Menu Older Adults Find Content COVID Health Falls Prevention Medicare Money Age Well Planner. Back to Main Menu Professionals Find Content Center for Benefits Access Center for Healthy Aging National Institute of Senior Centers Aging Mastery®. Find us on Social. Diabetes for Older Adults Older Adults and Diabetes: How Social Support Can Help Jul 29, 6 min read. Key Takeaways A supportive social network can help older adults make and maintain necessary behavior changes to manage their diabetes. The average household size including the adolescent was 4. The sample was primarily lower to upper middle class, with 1. All consecutive adolescents who received treatment for their diabetes over a 4-month period for routine check-ups or problems with diabetes at a children's hospital in the Midwest were invited to participate. Adolescents 11 to 18 years of age were recruited if they had had diabetes for at least 6 months and were accompanied by a parent or guardian who could provide informed consent. Ninety percent of the eligible families agreed to participate, and those who declined most commonly cited time constraints as the reason. Diabetes Social Support Questionnaire-Family Version. The DSSQ-Family copy available from first author was developed to assess adolescents' perceptions of family behaviors that are supportive for their diabetes care see Table I for a list of the items. The 58 items in the initial version were developed from several sources, including focus interviews with adolescents, interviews with health care providers, and prior research e. The frequency ratings 1 to 5 were identical to those used in the diabetes social support interview DSSI-Family; La Greca et al. The positive ratings 1 to 3 were identical to those used in the DSSI-Family; nonsupportive -1 and neutral 0 ratings were added, as the questionnaire assessed a wide range of family behaviors; not all of them may be viewed as supportive to adolescents. The DSSI-Family specifically asks the adolescent about supportive behaviors, so that ratings of neutral or nonsupportive are not necessary. DSSQ-Family: Adolescent Ratings of Supportiveness, Frequency, and Individualized Ratings Means and SD. Based on prior research e. These scores were calculated for all the DSSQ-Family items Total and for the five areas of diabetes care see the Results section for scoring details. The PSS assesses adolescents' perceived emotional support from family PSS-Family and friends PSS-Friends. Scores can range from 0 to 20, with higher scores reflecting greater emotional support. The PSS has been used with adolescents and adults who have diabetes La Greca et al. Previous research supports the reliability and validity of the instrument. Internal consistencies have ranged from. Emotional support from the family on the PSS-Family also has been found to correlate significantly with diabetes-specific support from family members La Greca et al. In this sample, the internal consistencies were. The FES is a widely used instrument that assesses family environment. It consists of 10 subscales, each with 9 true-false items; subscale scores can range from 0 to 9. The FES subscales have adequate internal consistency range from. Due to time constraints, only the Cohesion and Conflict subscales were used in this study, as they were of most interest. In this sample, their internal consistencies were. Adherence to Diabetes Care. Adherence was assessed using a structured interview developed by Hanson et al. Test-retest reliabilities over 3 and 6 months have been reported to be. Hanson et al. have provided data on the validity of this measure for adolescents with diabetes; in particular, higher levels of adherence have been significantly related to metabolic control Hb A1 assays , with correlations in the range of. The primary study objective was to develop and evaluate the DSSQ-Family. Prior to the main analyses, the 58 items were examined to determine their appropriateness for inclusion on the final questionnaire. That is, most adolescents did not view these items as supportive. The remaining 52 items that were retained on the DSSQ-Family appear in Table I. To examine a normative scoring approach, we calculated average frequency scores for the Total DSSQ-Family all 52 items and for the five areas of diabetes care insulin, blood testing, meals, exercise, emotions. Scores could range from 0 to 5 see Table I. To examine an individualized approach, for each adolescent, the frequency score for each item was multiplied by the corresponding supportiveness score i. Individualized scores averages were calculated for the Total DSSQ-Family and the five areas of diabetes care and could range from -5 not supportive but very frequent to 15 very supportive and very frequent. An initial study goal was to evaluate the two methods for scoring the DSSQ-Family. Internal consistencies 2 Cronbach's α were calculated. For the frequency ratings, internal consistencies were. Internal consistencies for the individualized ratings were slightly higher:. For the frequency ratings, retest reliabilities were. For the individualized ratings, retest reliabilities were. Intercorrelations among the DSSQ-Family scores were examined next. The frequency ratings were highly correlated with the corresponding individualized rating which was a combination of frequency and supportiveness ; these correlations ranged from. A second study goal pertained to concurrent validity. The associations between perceived family support for diabetes care and demographic variables age, disease duration, gender were examined, but only age-related differences in perceived family support for diabetes care were expected. Pearson correlations were computed for age and disease duration with the frequency and the individualized ratings on the DSSQ-Family see Table II. As expected, for the Total score, younger adolescents reported receiving more frequent support from family members for their diabetes care. In addition, for all five areas of diabetes management, the frequency of family support was significantly related to age, with younger adolescents perceiving more support than older adolescents. Identical findings were obtained for the individualized ratings. As expected, diabetes duration was unrelated to perceived family support. Gender differences were evaluated using one-way analyses of variance ANOVAs for each of the DSSQ-Family scores listed in Table II left side of the table , using an alpha level of. As expected, none of the measures of family support differed significantly for adolescent boys and girls. The means for the total sample were reported in Table I. DSSQ-Family Frequency and Individualized Ratings: Correlations With Age, Disease Duration, and Other Support Measures. As another way of evaluating concurrent validity, the associations between the DSSQ-Family and other measures of support from family and friends were examined. We hypothesized that the DSSQ-Family would be related to the general measures of family support PSS-Family, FES-Cohesion , but not to friends' support PSS-Friends or to family conflict FES-Conflict. This pattern was identical for the individualized ratings. Similar results were obtained for the five areas of diabetes management. In general, adolescents who reported more frequent family support for the specific areas of diabetes care also viewed their families as more emotionally supportive and more cohesive. An identical pattern was observed for the individualized ratings. Thus, regardless of whether the frequency or individualized ratings were used, more emotionally supportive and cohesive families were perceived as providing more diabetes-specific family support. In support of the discriminant validity of the DSSQ-Family, none of the frequency or individualized ratings was related to support from friends PSS-Friends or to family conflict FES-conflict. The only exception was that perceptions of emotional support for diabetes care were negatively related to family conflict. A third study goal was to examine the predictive validity of the DSSQ-Family, hypothesizing that greater perceived family support for adolescents' diabetes care would predict better adherence, even when controlling for general levels of families' emotional support. Two hierarchical regression analyses were conducted see Table III , with adherence as the dependent variable, and using either the Total frequency ratings or the Total individualized ratings as predictors. On the second step, family support and cohesion PSS-Family and FES-Cohesion were entered to control for general levels of family support and cohesion and to determine if more supportive, cohesive families had more adherent adolescents. In the third step, the diabetes-specific support scores were entered. Perceived Family Support for Diabetes Care as a Predictor of Adolescents' Treatment Adherence. Table III shows that younger adolescents had better adherence Step 1 , as did adolescents who perceived their families as more cohesive Step 2. Adolescents with greater perceived family support for diabetes care reported better adherence. Partial correlations controlling for age, family support, and cohesion indicated that greater family support for insulin administration. A final study goal was to examine the clinical utility of the DSSQ-Family by identifying the specific family behaviors that adolescents perceived as most supportive for their diabetes care. These 13 items are marked in Table I with a superscript a. The mean perceived supportiveness of the 13 items was 1. Underrepresented among the most supportive items were those dealing with insulin Across the 13 most supportive items, an average frequency score and an average individualized score were calculated. Their internal consistencies were. Regression analyses identical to those described were conducted for the 13 most supportive items as predictors of adolescents' adherence. Little research has examined the specific family behaviors associated with youngsters' disease management Drotar, , even though families play an important role in disease management and adaptation for youths with chronic pediatric conditions. Thus, information on family behaviors that relate to better treatment adherence for adolescents with diabetes has the potential to inform the next generation of family interventions for youths with diabetes. In this regard, this study presents a new measure and provides useful information on the family behaviors that adolescents perceived to be supportive for their diabetes care. This information may be useful for enhancing adolescents' treatment adherence. The primary study objective was to develop and examine the utility of a new measure, the DSSQ-Family, to assess adolescents' perceptions of family support for diabetes care. The results provided promising support for this measure. In particular, internal consistencies for the various DSSQ-Family scores were high, and the patterns of relationships with other measures were consistent with predictions. The results also provided support for the incremental and predictive validity of the individualized ratings from the DSSQ-Family, which predicted adolescents' adherence above and beyond general levels of family emotional support and cohesion. One important clinical implication of these findings is that the DSSQ-Family appears to be a useful measure of perceived family support for adolescents' diabetes care. In this regard, the DSSQ-Family may be useful to include in future studies of adaptation and disease management for youths with diabetes. In the process of evaluating the DSSQ-Family, two different scoring methods were examined: one based on a normative approach that utilizes frequency ratings for supportive behaviors, and one based on an individualized approach that adjusts the frequency ratings for the individual adolescents' perceptions of supportiveness. Although the findings were very similar for the two methods, the results appeared to favor the individualized ratings. These findings suggest that the individualized approach may be more useful than the normative approach in clinical settings. In particular, efforts to increase family support for adolescents' diabetes care may be better served by including adolescents' own perspectives on what they view as supportive, rather than relying on what adolescents typically view as supportive. Another key finding from this study, supporting the concurrent validity of the DSSQ-Family, was that older adolescents perceived their family members to provide less diabetes-specific support than did younger adolescents. Others e. One of the potential benefits of a measure such as the DSSQ-Family is that it may be used to identify family behaviors that adolescents do find to be supportive, so that family members can provide appropriate kinds of support and maintain involvement in diabetes care as adolescents mature. In contrast to the findings for age, disease duration was not related to perceived family support for diabetes care. Thus, the relationship between age and perceived family support cannot be explained by the fact that younger adolescents typically have had diabetes for a shorter period of time and, therefore, need more assistance with their diabetes care. In further support of the concurrent validity of the DSSQ-Family, the results revealed that adolescents who perceived their families as providing more diabetes-specific support also viewed their families as more cohesive and emotionally supportive. In contrast, adolescents' perceptions of family support for diabetes care were not related to adolescents' support from friends or to reports of family conflict, in general. Although further replication of these findings would be desirable, these data do provide good preliminary support for the convergent and discriminant validity of the DSSQ-Family. Furthermore, from a clinical perspective, it was interesting to note that the correlations between diabetes-specific family support and general family support and cohesion were moderate. This suggests that even cohesive, emotionally supportive families do not necessarily provide high levels of diabetes-specific support. This was especially true for family support for adolescents' exercise, which was unrelated to family cohesion. A clinical implication of these findings is that even supportive, cohesive families may need help in identifying specific ways to support adolescents' diabetes care. With respect to the predictive and incremental validity of the DSSQ-Family, a key finding was that the individualized ratings from the DSSQ-Family predicted adherence above and beyond the more generic measures of family support and cohesion. In fact, the general measure of family support was not significantly related to adherence, when adolescent age was controlled. Pediatric investigators have emphasized that disease-specific measures may be helpful in understanding youngsters' disease management and disease adaptation e. Furthermore, the specific areas of diabetes-related family support that were most associated with adolescents' adherence involved daily management tasks meals, glucose testing, and insulin administration , rather than exercise or emotions. Although family members' support of management tasks may be important for adherence, their provision of emotional support may also be critical. In the future, it may be fruitful to examine linkages between families' emotional support for diabetes and other indices of disease adaptation and adjustment. Although our findings were promising, continued study of the DSSQ-Family is desirable. In particular, several study limitations suggest directions for further investigation. First, in this study it was not possible to obtain retest reliability for the DSSQ-Family, and this will be important in future work. Second, and also important for future research, would be a replication of the study results with a larger sample, especially one that has sufficient power to factor analyze the DSSQ-Family. Third, this study relied on adolescents' reports of family support and treatment adherence. Nevertheless, in future studies it will be desirable to evaluate support and adherence from multiple perspectives e. Fourth, this study focused on a primarily middle-class sample, with a relatively small number of minority youths, and thus can best be generalized to similar groups of adolescents. In the future, work on the DSSQ-Family should be extended to multiethnic, low-income adolescents with diabetes. One advantage of a checklist measure, such as the DSSQ-Family, is that it may facilitate comparisons across different ethnic groups because of its standard set of items. Finally, this study focused on a particular chronic disease, although it is likely that the finding might be applicable to other chronic conditions for which medications, exercise, or meal management play a role. Future studies may wish to adapt the DSSQ-Family for other chronic pediatric conditions. In conclusion, this study offers the DSSQ-Family as a useful instrument for understanding family members' support of adolescents' diabetes care. An important clinical implication is that continued family involvement in the day-to-day management of diabetes may be critical for youngsters' disease management. At least when the goal of intervention is to promote treatment adherence, it may be most productive to focus on ways that families can support daily management tasks, taking into account what the individual adolescent perceives to be supportive in these areas. This may be especially critical for older adolescents, as families are substantially less likely to be supportive of older teens' management tasks, as the data in this study have shown. The key issue is not whether families should be involved and supportive, but how best to do this, especially as adolescents' mature. Preparation of this paper was supported, in part, by grants from the National Heart, Lung, and Blood Institute HL and the National Institute of Child Health and Development T32 HD We thank the following individuals for their input on the initial development of the DSSQ-Family: Edwin Fisher, Jr. Anderson, B. Assessing family sharing of diabetes responsibilities. Journal of Pediatric Psychology , 15 , Family characteristics of diabetic adolescents: Relationship to metabolic control. Diabetes Care , 4 , Anderson, R. The prevalence of comorbid depression in adults with diabetes: A meta-analysis. Diabetes Care , 24 , Bearman, K. 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Journal of Pediatric Psychology , 17 , Social competence and parental support as mediators of the link between stress and metabolic control in adolescents with insulin-dependent diabetes mellitus. Journal of Consulting and Clinical Psychology , 55 , Hauser, S. Milley, J. Adherence among children and families with insulin-dependent diabetes over a four-year longitudinal follow-up. Kaslow, N. Empirically validated family interventions for pediatric psychology: Sickle cell disease as an exemplar. Kazak, A. La Greca, A. I get by with a little help from my family and friends: Adolescents' support for diabetes care. Journal of Pediatric Psychology , 20 , Developmental and behavioral aspects of diabetes in children and adolescents. Children's Health Care , 19 , Assessment as a process in pediatric psychology. Journal of Pediatric Psychology , 21 , Lyons, J. Perceived social support from family and friends: Measurement across disparate samples. 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| Friends, Family & Diabetes | Diabetes | CDC | Schiotz Fog, Bogelund M, Willaing I. Journal of Osteopathic Medicine, Vol. Chronic disease self-management within the monthly benefit cycle of the Supplemental Nutrition Assistance Program. All issues. The measurement of observer agreement for categorical data. |
Metrics preventino. Diabetes is a Anti-pathogen measures illness which requires lifelong Restorative techniques behaviors. Diqbetes objective of diabetds present research was prevenfion Low GI smoothies the Social support for diabetes prevention of self-efficacy, attitude and social support with adherence to diabetes self-care behavior. In this cross-sectional study conducted indiabetic patients of Zarandieh, Iran participated. They were evaluated by valid and reliable questionnaires comprised of items on diabetes self-care, self-efficacy in dealing with problems, social support and attitude towards self-care.
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