Abstract
Objectives: The main purpose of this work is to study diabetes mellitus and stroke in the United States during the years 2007-2017 and to find not only statistically significant predictors for diabetes, but also a possible association between diabetes and stroke.
Methods: Chi-square test and One-way analysis of variance (ANOVA) were the statistical methods used to derive the results of this work in order to check the statistical significance of diabetes mellitus in relation to patients’ socioeconomic factors. In addition, a multivariate logistic regression analysis was used to obtain odds ratio and find statistically significant prognostic factors for both diabetes and stroke.
Results: According to multiple logistic regression analysis, the risk for diabetes mellitus is four times higher in widowed men and two times higher in unemployed male subjects who had previously worked. In addition, marital status and employment have been shown to be prognostic risks for stroke.
Conclusion: The results describe for the first time the importance of deprivation (of work and partner) as a primary prognostic risk factor for diabetes. Moreover, the same factor was proved to be the primary prognostic risk factor for both stroke and diabetes, which implies a nexus between diabetes mellitus and stroke.
Keywords:prognostic factors, diabetes mellitus, stroke, socioeconomic factors.
INTRODUCTION
The incidence of diabetes mellitus is rapidly increasing worldwide. More specifically, diabetes mellitus ranks as the ninth leading cause of death globally, with an estimated 415 million new cases in 2015 (1). According to the International Diabetes Federation (IDF), 1 in 11 adults aged 20–79 had diabetes mellitus in 2015, 90% of whom having type 2 diabetes mellitus (2). This is due to population aging and growth, but also to changes in prevalence of the main risk factors for diabetes, several of which are associated with socioeconomic development (3-5). Low socioeconomic status is associated with increased incidence and mortality from type 1 diabetes or insulin-dependent diabetes mellitus (6), mainly due to non-attendance to intensive insulin regimen (7), non-monitoring blood glucose levels (8), and complications arising from diabetes (9, 10). On the other hand, low socioeconomic status of patients with type 2 diabetes is associated with cardiovascular complications, which are the leading cause of morbidity and mortality from this type of diabetes (4). Moreover, low education is associated with an increased prevalence of type 2 diabetes, while retired people and persons working in white collar jobs were reported to have a higher risk of this type of diabetes (11).
Prior studies have found an increased risk of stroke in patients with diabetes (12-18). More specifically, it has been found that the risk for stroke posed by diabetes mellitus was about four times higher (19). There are several underlying mechanisms wherein diabetes leads to stroke, including vascular endothelial dysfunction, increased early-age arterial stiffness, systemic inflammation and thickening of the capillary basal membrane (20).
This work studies diabetes mellitus and stroke in the United States (US) between the years 2007 and 2017 in order to find statistically significant predictors for diabetes and a possible link between diabetes and stroke.
MATERIALS AND METHODS
The data used in this work come from the National Health Interview Survey (NHIS) dataset ) and cover the period 2007–2017. The target population for NHIS is the civilian non-institutionalized population of the US. NHIS data are collected through personal household interviews. The main objective of NHIS is to monitor the health of the US population through the collection and analysis of data on a broad range of health topics. The number of examined adult patients with diabetes mellitus was 232.653. Moreover, in the geographic classification of the US population, states are grouped into four regions used by the US Census Bureau:
- Northeast: Maine, Vermont, New Hampshire, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and Pennsylvania.
- Midwest: Ohio, Illinois, Indiana, Michigan, Wisconsin, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Kansas, and Nebraska.
- South: Delaware, Maryland, District of Columbia, West Virginia, Virginia, Kentucky, Tennessee, North Carolina, South Carolina, Georgia, Florida, Alabama, Mississippi, Louisiana, Oklahoma, Arkansas, and Texas.
- West: Washington, Oregon, California, Nevada, New Mexico, Arizona, Idaho, Utah, Colorado, Montana, Wyoming, Alaska, and Hawaii.
Statistical analysis
To extract the results of this work, two statistical methods – Chi-square test for categorical and One-way analysis of variance (ANOVA) for continues variables – were used in order to check the statistical significance of diabetes in relation to patients’ socioeconomic characteristics such as age, race, origin, education, family income, poverty status, health insurance coverage, place of residence and region. Factors that determine the prevalence of diabetes were assessed by using multiple logistic regression analysis. To assess the predictors of diabetes, we used data from patients with a new diagnosis of diabetes compared to a matched cohort of patients without diabetes. More specifically, the control group included target population without diabetes with the same socioeconomic characteristics as the patient group. Data were weighted prior to analysis. Predictors were represented using odds ratio (OR) and 95% confidence intervals, and P < 0.05 was considered to be statistically significant. The study was carried out using IBMSPSS 25 software package for Windows.
RESULTS
To check the zero hypotheses that the mean of diabetes mellitus patients in the US did not differ according to their socioeconomic characteristics, the Chi-square test and One-way analysis of variance (ANOVA) were used. As shown in Table 1, there is a statistically significant difference in the number of diabetes patients in relation to both gender and age, the disease occurring mainly in men (50.1%) aged 45-64 (46.5%) and having the greatest frequency in white race people (78.9%), not Hispanic or Latino (45.2%) persons. The following socioeconomic characteristics were found to be statistically significant: “High school diploma” for education (30.4%), “Not employed but has previously worked” for employment status (42.7%), “not poor” for poverty status (61.7%), the range of $35.000 or more for family income (35.8%), private health insurance in age groups under 65 (57.2%) and 65 and over (49.1%) for health insurance coverage, “married” for the marital status (56.7%), “South” for the region with the highest occurrence of diabetes (40%) and a population size of one million or more (48.9%).
Table 2 shows the multiple logistic regression analysis and odds ratios in order to find the predictors for the occurrence of diabetes mellitus.
As shown in Table 2, all prognostic factors are statistically significant (p<0.05). According to multiple logistic regression, the risk of diabetes is significantly higher in men (OR 1.08), age group of 65-74 (OR 1.1), Black or African American race (OR 1.6) and “less than a high school diploma” education status (OR 3.0). Moreover, unemployed people who have previously worked had two times the risk of developing diabetes (OR 1.9). In addition, the risk of diabetes is significantly higher with “less than $35.000” family income (OR 2.4), “near poor” poverty status (OR 1.52), and health insurance coverage – “other coverage” in the age group under 65 (OR 3.3) and “Medicare and Medicaid” in the age group of 65 and over (OR 1.5). Widowed adults have higher risk of developing diabetes (OR 4.5). Finally, the risk of diabetes is significantly higher with “South” region (OR 1.25) and “not in Metropolitan statistical area” place of residence (OR 1.0).
Figure 1 shows the trends in diabetes and stroke between the years 2007 and 2017 in the United States. The incidence of both diseases continues to increase during this period.
In order to find a possible link between diabetes and stroke, a multivariate logistic regression analysis was used for stroke patients. As can be seen from Table 3, marital status plays a crucial role in the incidence of stroke. Widowed adults have the highest risk for the occurrence of stroke (OR 6.0). Family income and education are also prognostic risks for stroke; more specifically, “less than $35,000” family income (OR 4.0) and “less than a high school diploma” education status (OR 3.7) have a four times higher risk for stroke. Finally, unemployed adults who have previously worked have two times the risk of stroke (OR 1.9). Moreover, the risk of stroke is significantly higher with female gender (OR 1.0), age over 75 (OR 1.0), Black or African American race (OR 2.4), poverty status (“near poor”) (OR 2.0), health insurance coverage (“other coverage” under 65 years old and “Medicare and Medicaid” over 65) (OR 5.6 and 1.3, respectively), region (“South”) (OR 1.32) and place of residence (“not in Metropolitan statistical area”) (OR 1.0).
DISCUSSION
Increasing attention should be given to prognostic factors that had the highest odds ratio. It is noted that marital status is the socioeconomic characteristic of diabetes mellitus patients with the highest risk; more specifically, it was found that widowed adults had the highest risk of developing diabetes (OR 4.5). Moreover, education plays a crucial role in developing this type of disease. Adults with “less than a high school diploma” have a three-fold increased risk of developing diabetes (OR 3.0). Finally, employment is a prognostic risk for this type of disease, as unemployed adults who have previously worked were found to have a two-fold higher risk for diabetes (OR 1.9).
It is also noteworthy that stroke patients with the highest OR had the same socioeconomic characteristics as those of diabetes mellitus patients. Deprivation of work and partner proved to be the primary prognostic risk factor for both stroke and diabetes, which implies a link between diabetes and stroke.
The importance of this study lies in the association of multiple socioeconomic variables with diabetes and stroke, which reflects the complexity and multidimensional nature of deprivation as well as the various roles of these dimensions during the course of life, which in turn reflects the longest gestation period for both diabetes and stroke. More specifically, we found that partner and work deprivation, two determinants in the life of an adult, are rapidly increasing the risk of diabetes as well as stroke. We found that not only deprivation but also partner’s death plays a key role in the increased risk of developing these two diseases.
CONCLUSION
This paper has highlighted that different socioeconomic variables were associated with different risks of diabetes mellitus, while deprivation (of work and partner) proved to be the primary prognostic risk factor for diabetes. Moreover, the same factor was shown to be the primary prognostic risk factor for stroke as for diabetes, which implies a link between diabetes and stroke.
Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Conflict of interests: none declared
Financial support: none declared.
FIGURE 1.
Trends in diabetes mellitus and stroke during 2007-2017 in the United States
TABLE 1.
Chi-square and One-way Anova test
TABLE 2.
Statistically significant predictors of diabetes in the US using multivariate logistic regression
TABLE 2.
Statistically significant predictors of diabetes in the US using multivariate logistic regression
TABLE 3.
Statistically significant predictors of stroke in the US using multivariate logistic regression
TABLE 3.
Statistically significant predictors of stroke in the US using multivariate logistic regression
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