Gender Differences in Medical Advice and Health Behavior of Obese African Americans With and Without Type 2 Diabetes

Abstract

This study examined gender differences in medical advice related to diet and physical activity for obese African American adults (N = 470) with and without diabetes. Data from the 2007-2008 National Health and Nutrition Examination Survey were analyzed using logistic regression analyses. Even after sociodemographic adjustments, men were less likely to report receiving medical advice as compared with women. Both men and women given dietary and physical activity advice were more likely to follow it. Men were less likely to report currently reducing fat or calories, yet men with diabetes were 5 times more likely to state that they were reducing fat and calories as compared with women with diabetes. Gender- and disease state–specific interventions are needed comparing standard care with enhanced patient education. Moreover, these findings necessitate studies that characterize the role of the health care professional in the diagnosis and treatment of obesity and underscore patient–provider relationships.

Keywords

medical advice gender disparities obesity type 2 diabetes African Americans

Obesity, a preventable chronic disease, has become a major public health problem, contributing to an estimated 112,000 preventable deaths per year, with the majority (84,000) occurring in persons ≤70 years old (Flegal, Graubard, Williamson, & Gail, 2005). Obesity has been well-established as a risk factor for other chronic diseases, including diabetes, hypertension, coronary heart disease, and some cancers, such as endometrial, breast, prostate, and colon; obese adults are at increased risk for high cholesterol, gallbladder disease, osteoarthritis, sleep apnea, and respiratory problems (U.S. Department of Health and Human Services, 2010). The cost of obesity is staggering and places an undue burden on the health care system (Finkelstein, Trogdon, Cohen, & Dietz, 2009).

African American men have the highest rate of obesity as compared with Mexican American and non-Hispanic Caucasian men (Centers for Disease Control and Prevention [CDC], 2010a; Flegal, Carroll, Ogden, & Curtin, 2010). Obesity can lead to type 2 diabetes and cardiovascular diseases (including coronary heart disease and stroke) and is of particular concern for African American men, whose death rate from coronary heart disease is twice that of non-Hispanic Caucasian men (Kochanek, Xu, Murphy, Miniño, & Kung, 2011). Furthermore, diabetes, an independent risk factor of cardiovascular diseases, is twice as likely in African Americans (13.2%) as in non-Hispanic Caucasians (6.4%) (CDC, 2010b).

Health behaviors are largely responsible for the onset of cardiovascular diseases such as obesity and diabetes. Effective patient–provider health communications, quality of treatment, health utilization, and continuity of care, have the potential to affect health behavior. Health care systems can play a vital role in reversing obesity, preventing diabetes, and reducing diabetes complications (notwithstanding cardiovascular disease) by helping patients with lifestyle changes in diet and exercise. Following medical recommendations in diet and physical activity can be challenging and require support from health care professionals (Bardia, Holtan, Slezak, & Thompson, 2007). Poorer quality of treatment may be partly attributed to lower percentage of board-certified physicians treating African Americans as compared with Caucasian patients, adjusting for health utilization (Bach, Hoangmai, Schrag, Tate, & Hargraves, 2004).

Successful obesity management and prevention requires extensive treatment and counseling about healthy diet, exercise, and overweight (Agency for Healthcare Research and Quality [AHRQ], 2011). Oftentimes, the extent of counseling is by physicians’ or other health care professionals’ simple instructions for weight loss; albeit, brief encouragement for health behavior change has been shown to have some benefit (Ha, Nguyen, Kyriakos, Markides, & Winkleby, 2011; Truswell, 2000; U.S. Department of Health and Human Services, 2001, 2010). Most of these studies in obesity management have not been performed in African American populations. The low adherence to dietary and exercise change for these populations suggest the need for longitudinal intervention studies specifically designed for African Americans by gender and disease state. Findings from two studies of medical advice and corresponding behaviors are as follows: 30% (dietary changes, only) for a White, European population (Haslam et al., 2000) and for adults with type 2 diabetes, adherence to dietary advice was 8%, and physical activity recommendation was 6% exercise across 13 countries in Asia, Australia, Europe, and North America (Peyrot et al., 2005).

Race/ethnicity, gender, and diabetes status have been shown to be social determinants in health care disparities and utilization. According to U. S. Census estimates, 20% of African Americans were classified as uninsured during both 2004 and 2008, representing significantly higher uninsured rate as compared with non-Hispanic Caucasians (14.1%; Moonesinghe, Zhu, & Truman, 2011). Health care utilization is another social determinant of health that may vary by gender and race. However, racial and ethnic disparities in health care exist even when insurance status, income, age, and disease state are comparable (Nelson, 2002). Health disparities have been primarily attributed to sociocultural barriers based on extensive governmental and academic studies. Betancourt, Green, Carrillo, and Ananeh-Firempong (2003) defined sociocultural barriers contributing to racial/ethnic disparities in health and health care as complex and classified them into three broad categories. Organizational, structural, and clinical organizational barriers refer to the unequal racial/ethnic composition of the medical and health care workforce as compared with the U.S. population. Within structural barriers are lack of culturally or linguistically appropriate health education materials and services, disproportionately long waiting times for appointments, and, problems with access to specialists and continuity of care. Clinical barriers occur when there is an ineffective interaction between the health care provider and patient (inadequate patient–provider relationship).

More sociocultural barriers may be perceived by African American men as compared with African American women. Barriers of effective medical treatment for African Americans have been studied primarily as gender-specific by focus groups and survey. There are numerous barriers to seeking medical care shared by African American men and women, such as concerns of missing work, mistrust of health care providers and the health care system, lack of preventive care information, and institutional racism (Fatone & Jandorf, 2009; Griffith, Allen, & Gunter, 2011 and references therein). African American men face additional barriers to seeking medical care, such as lower health care utilization than women, lack of habitual health care, delaying necessary medical treatment, fear of negative diagnosis and negative reports of health care from friends or family (Griffith et al., 2011 and references therein). Male gender socialization decreases the likelihood of African American men seeking medical care and following medical advice (Griffith et al., 2007 and references therein).

Not only are African American men less likely to seek medical treatment than African American women, but there is also some evidence to suggest that physicians’ advice may differ by gender (Anderson et al., 2001; Loureiro & Nayga, 2006). Males from the Behavioral Risk Factor Surveillance System (BRFSS) data, regardless of race or body mass index (BMI), were less likely to report being given advice to lose weight as compared with females (Loureiro & Nayga, 2006). On the other hand, physicians given hypothetical patient cases were more likely to advise male patients with BMIs of 32 kg/m² to lose weight than female patients of the same BMI; yet the same physicians are more likely to advise female patients with BMIs of 25 kg/m² to lose weight as compared with their male counterparts (Anderson et al., 2001). Such findings suggest physicians’ attitudes toward treatment, education, and specific interventions may differ based on the gender of the patient.

Patient–provider relationship, an important clinical social determinant of health, has been measured by degree of the provider’s cultural competency. Social determinants of health include the health care system and refer to the conditions under which people are born, live, and age (World Health Organization [WHO], 2012). To reduce health disparities, the organization and health care provider need to approach the patient with cultural competency. Cultural competency has been defined as an evolving process of awareness and skills that incorporates values, principles, behaviors, attitudes, and policies of working effectively cross-culturally (Cross, Bazron, Dennis, & Isaacs, 1989). Perceptions and experiences of medical care have been associated with adherence to medical recommendations (Griffith et al., 2011). Patients who trust their physicians are more likely to follow medical advice (Griffith et al., 2011; Safran et al., 1998).

Patient adherence to education and treatment interventions has been positively associated with effective provider communication throughout the literature since the late 1960s (McCann & Blossom, 1990). However, providers’ communication has been found to be more effective for females (Roter, Lipkin, & Korsgaard, 1991), non-Hispanic Caucasians, employed, and more educated persons as compared with their counterparts (Thornton, Powe, Roter, & Cooper, 2011 and references therein).

Although medical advice to improve diet and exercise are warranted for most populations suffering from chronic disease, literature is lacking as to whom physicians give advice and which sociodemographic factors are associated with receiving advice. Whether or not advice was given has also been associated with physicians’ characteristics. An in-depth qualitative analysis revealed that certain physicians believed family, social, community, and other environmental factors influenced the obesity epidemic and did not feel their intervention was effective (Leverence, Williams, Sussman, & Crabtree, 2007). Furthermore, there is a scarcity of literature concerning gender-specific differences in client health teaching of obese African Americans by physicians.

Purpose and Hypotheses

The purpose of this study was to examine gender differences in medical advice related to diet and physical activity for obese African American adults (N = 470) with and without diabetes. Since the prevalence of obesity is higher for African American women (49.6%) as compared with African American men (37.3%) (CDC, 2010a; Flegal et al., 2010), health care providers may be selectively encouraging obese African American women to modify their diet and physical activity level and not giving the same advice to their male counterparts. For those with diabetes, medical advice to reduce fat or calories as well as to increase physical activity is standard care (American Diabetes Association, 2011). These differences in patient–provider relationships and communication between genders underscore the need to explore these associations. This article explores within race, gender comparisons of medical advice and behavior for (a) obese African Americans free of diabetes and (b) obese African Americans with diabetes by the following hypotheses:

Hypothesis 1: Obese African American women will be more likely to report receiving medical advice to (a) reduce fat or calories and (b) to increase physical activity as compared with obese African American men.

Hypothesis 2: Medical advice to (a) reduce fat or calories and (b) increase physical activity will be more likely for persons with diabetes, but independent of gender and gender by diabetes.

Several studies have reported patients receiving medical advice were more likely to follow the recommendations, independent of race, gender, and other social factors (Deakin, Cade, Williams, & Greenwood, 2006; Phili-Tsimikas et al., 2004; Tang et al., 2005; Tang, Funnell, Brown, & Kurlander, 2010). Therefore, we hypothesize that gender will not be a factor in level of following advice.

Hypothesis 3a: Obese African Americans who report receiving medical advice to reduce fat or calories will be more likely to report currently reducing fat or calories, independent of gender and diabetes status.

Hypothesis 3b: Obese African Americans who report receiving medical advice to increase physical activity will be more likely to report now increasing physical activity, independent of gender and diabetes status.

Method

Source of Data

This study extracted data from the 2007-2008 National Health and Nutrition Examination Survey (NHANES) that are available for public use (NHANES, 2011a, 2011b). Each survey period applies a complex, stratified, multistage probability cluster sampling design to obtain a nationally representative sample of the U. S. civilian, noninstitutionalized population. This survey contains data for 10,149 individuals of all ages and is generated under the auspices of the National Center for Health Statistics (NCHS), Division of Health and Nutrition Examinations Surveys (DHNES), part of the CDC. All participants read, understood, and signed informed consent forms. Separate informed consent forms were signed for participants depending on whether they participated in the interview and health examination or just the interview. For this study, the sample weight chosen was for the health examination and was designed to account for unequal probabilities of selection, account for nonresponse, and to conform to a known population distribution. Weight and height were measured in a mobile examination center using standardized techniques and equipment. BMI was calculated as weight in kilograms divided by height in meters squared (kg/m²), rounded to the nearest tenth. Detailed information concerning the data collection procedure for this cross-sectional survey are found at the website (see reference, NHANES, 2011a, 2011b).

Description of Sample

There were a total of 9,990 men and women, aged 21 years or older, of whom, 5,692 were interviewed and examined. From this data set, filters were applied to examine the ethnic/racial category “Black non-Hispanic” (n = 1,209). The designation “Black non-Hispanic” is synonymous with African American (originating from African or the Caribbean and of non-Latin descent) since participant in NHANES studies self-report race and ethnicity as separate responses.

Participants missing weight or height measurements (n = 27; 2.2%) were excluded from the analyses. Obesity was operationalized using BMI ≥ 30 kg²/m and yielded a final sample size of 470 obese African American men and women, with and without diabetes. Since there is no established effect size for power estimation, a priori sample size estimation was used. To be considered reliable estimates of the population studied, the following parameters were chosen for each logistic regression: 70% correct classification of the cases for the outcome variables and a design effect of not more than 2 for gender.

Study Design

This study selected a population categorized as obese (BMI ≥ 30 kg/m²) rather than the combined category of overweight/obese (BMI ≥ 25 kg/m²). There are several limitations to consider when combining the “overweight” and “obese” BMI categories: (a) Findings may be different for these groups; (b) the “overweight” classification may be inaccurate for persons with high muscle mass to fat ratio (lower percentage body fat) and these misclassifications may be greater for men than women; and (c) despite the fact that research concerning the association of patients’ characteristics and medical advice for diet and exercise has included both categories of patients, combined: overweight and obese (Eakin, Brown, Shofield, Mummery, & Reeves, 2007; Hinrichs et al., 2011; Ma, Urizar, Alehegn, & Stafford, 2004), there may be differences in advice given to men and women within each of these categories (Anderson et al., 2001). Additionally, several studies have questioned the accuracy of the “overweight” classification (Ha et al., 2011 and references therein).

Main Independent Variables and Covariates

Gender and diabetes status (with or without diabetes) were the main independent variables used for all hypotheses and were by self-report. Three diabetes-related questions from NHANES were used to create the variable “diabetes”: (a) a diagnosis of diabetes by a doctor or health care professional, (b) age of diagnosis, and (c) year of diagnosis. An affirmative response to all three questions was sufficient to use as a filter for “having diabetes.” Hypothesis 3 included the main effects of medical advice, diabetes status, gender, and their interactions. Health-related, sociodemographic variables included in the analyses as covariates were age, health insurance status, marital status, and education. Currently, smoking and language preference were tested since they may have influenced health care access. The model fit did not allow retention of either covariate. The variable for age was continuous; education was a categorical variable (ninth grade, some high school, high school graduate or GED, some college, college degree, and/or graduate school), reporting having current health insurance (in the past 12 months) was a binary variable (yes/no), and, marital status was collapsed into a binary variable: either currently married or living with a partner, or single, which included widowed, divorced, or never married (yes/no).

Major Variables

Independent variables

To examine the association of gender with medical advice about diet and exercise, the following questions from NHANES were used. Participants responded yes or no to each question: “To lower your risk for certain diseases, during the past 12 months have you ever been told by a doctor or health professional”: (a) “to reduce fat or calories in your diet”; and (b) “to increase your physical activity or exercise?”

Dependent variables

The relationship between gender and gender-specific medical advice about diet and exercise was examined based on participants’ responses to the following questions from NHANES: “To lower your risk for certain diseases, are you now doing any of the following: Reducing the amount of fat or calories in your diet?—or increasing your physical activity or exercise?”

Data Analysis

All data were analyzed applying the Mobile Examination Survey (MEC) 2-year sample weights using the Statistical Package for Social Science (SPSS, Version 18) with the module for complex design analysis. All analysis took into account differential probabilities of selection and the complex sample design, with SPSS, using the Taylor series linearization. A p value of less than .05 (two-sided) was considered statistically significant. Participants’ characteristics were presented by frequency and percent. Separate hierarchical logistic regression complex analyses were conducted for each of the major outcomes with the covariates discussed above. The first step included gender as the independent and the second step added diabetes and the interaction of diabetes by gender.

Results

The demographics of the study population are presented in Table 1. All participants were obese, having (BMI ≥ 30 kg/m²) and approximately one fourth had diabetes (23.2% males/25.1% females). Men were significantly younger, less likely to have health insurance, and had significantly different distribution of BMI than women. More than 20% of the combined sample (male and female African Americans in the obese weight range) had diabetes. A greater percentage of females reported having health coverage as opposed to males. There were no statistically significant differences in education, average age diagnosed with diabetes, and smoking between sexes (gender).

Table 1.

Characteristics of the Sample by Gender

	Male (n = 194)		Female (n = 276)
Variable	Mean	SE	Mean	SE	p
Age^a	45.1	0.82	47.0	0.82	.043
	%	SE	%	SE
Body mass index (kg/m²)					.014
30-35	61.3	3.2	47.3	4.4
>35	38.7	3.2	52.7	4.4
Current smoker (yes)	22.0	2.6	21.0	3.0	.780
Has diabetes (yes)	23.2	2.4	25.1	2.1	.347
Age diagnosed (years)	46.2	1.3	44.3	1.9	.393
Education					.223
<9th grade	3.5	0.9	4.1	0.7
9th-12th grade (no diploma)	18.4	2.9	25.3	3.7
High school graduate or GED	33.7	3.6	21.5	2.7
Some college	27.5	4.1	33.0	3.1
College graduate or above	16.9	3.8	16.1	3.0
Covered by health insurance (yes)	72.9	2.8	82.6	1.9	.014
Married/partnered (yes)	62.5	3.7	35.3	2.9	<.001
Never advised to reduce fat or calories—combined	57.1	3.4	32.9	3.9	.001
Never advised to increase physical activity or exercise	55.6	2.5	31.9	3.2	<.001

Note. The test of independence was analyzed by complex analyses. The estimates were based on χ² between groups (male and female) for categorical variables and the Wald F for age and age diagnosed with diabetes. The results are presented by the estimates: percentage of the population and standard error. N = 470 for the unweighted sample. Married or partnered was created by combining the two categories for yes and other marital status (widowed, divorced, single) was considered as “currently single.”

Age represents population average and standard error.

Gender, Diabetes Status, and Medical Advice

The final adjusted models are presented in Tables 2 and 3. The results indicate that obese men were less likely to receive medical advice for diet and exercise as compared with obese women. Those participants who had diabetes (and were obese) were advised regardless of gender. Several demographic characteristics were significantly related to receiving medical advice. Older age and higher education were attributes that were associated with receiving medical advice for diet and physical activity. Having health insurance was associated with a recommendation to increase physical activity but not to reduce fat or calories.

Table 2.

Logistic Regression Analyses Assessing Gender and Diabetes With Dietary Medical Advice

	Medical advice to reduce fat/calories
	Model 1: Without diabetes		Model 2: With diabetes
Variables	OR [95% CI]	p	OR [95% CI]	p
Male	0.39 [0.22, 0.67]	.003	0.32 [0.15, 0.65]	.003
Health insurance	1.19 [0.86, 1.85]	.268	1.18 [0.81, 1.71]	.348
Age	1.04 [1.02, 1.05]	<.001	1.02 [1.01, 1.04]	.007
Education (lowest)	0.27 [0.08, 0.90]	.038	0.25 [0.08, 0.80]	.012
Diabetes (yes)			3.19 [1.77, 5.77]	<.001
Diabetes by gender				.110
Model summary	F = 17.7 (7, 6), p = .001; R² = .180		F = 33.3 (9, 4), p = .002; R² = .254

Note. Models are based on a design of 12 degrees of freedom and the Wald F. The Nagelkerke pseudo R² represents the part of the variance of medical advice outcomes that is explained by the model. OR = odds ratio; 95% CI = 95% confidence interval.

Table 3.

Logistic Regression Analyses Assessing Gender and Diabetes With Medical Advice to Exercise

	Medical advice to increase physical activity/exercise
	Model 1: Without diabetes		Model 2: With diabetes
Variables	OR [95% CI]	p	OR [95% CI]	p
Male	0.38 [0.25, 0.61]	.001	0.31 [0.18, 0.54]	.008
Health insurance	1.52 [1.11, 2.06]	.012	1.55 [1.05, 2.27]	.029
Age	1.04 [1.03, 1.05]	<.001	1.02 [1.02, 1.03]	.001
Education (lowest)	0.11 [0.02, 0.81]	.003	0.09 [0.01, 0.73]	.001
Diabetes (yes)			3.92 [2.36, 6.49]	<.001
Diabetes by gender				.088
Model summary	F = 36.4 (7, 6), p < .001; R² = .204		F = 29.2 (9, 4), p = .003; R² = .298

Note. OR = Odds ratio; CI = Confidence interval.

The Effect of Receiving Advice on Behavior by Gender and Diabetes Status

The final logistic regression models for receiving advice and performing the behavior are presented in Table 4. Each behavior, reducing fat or calories and increasing physical activity and exercise was more likely for participants who reported being advised. The effect was not independent for gender and diabetes status for reducing fat or calories. Males with diabetes were five times more likely to state that they were reducing fat and calories as compared with females with diabetes. Being recommended to increase physical activity was independent of gender and diabetes status.

Table 4.

Logistic Regression Analyses Assessing Medical Advice With Behaviors by Gender and Diabetes Status

	Dependent variables
	Currently reducing fat/calories		Currently increasing physical activity/exercise
Independent variables	OR [95% CI]	p	OR [95% CI]	p
Given advice	3.76 [2.28, 6.19]	<.001	2.32 [1.66, 3.25]	<.001
Male	0.36 [0.19, 0.69]	.005	0.79 [0.42, 1.51]	.441
Health insurance	0.80 [0.36, 1.76]	.554	1.09 [0.52, 2.31]	.805
Age	1.02 [1.00, 1.04]	.030	0.98 [0.96, 1.00]	.091
Education (lowest)	0.31 [0.08, 1.31]	.104	—	—
Married or living with a partner	2.44 [1.42, 4.19]	.004	1.51 [0.96, 2.38]	.700
Diabetes	0.62 [0.34, 1.12]	.101	0.94 [0.48, 1.86]	.852
Gender × diabetes (male with diabetes)	5.10 [2.19, 11.9]	.001	1.55 [0.82, 2.93]	.162
Model summary	F = 51.0 (11, 2), p = .019; R² = .263		F = 4.83 (7, 6), p = .037; R² = .096

Note. Models are based on a design of 12 degrees of freedom and the Wald F; The Nagelkerke pseudo R² represents the part of the variance of following medical recommendations that is explained by the model. The model for physical activity included the full population (with and without diabetes), N = 470; however, to achieve a significant model fit, education was removed. The models present gender, diabetes, and all covariates.

Discussion

Medical advice is an important factor in health behavior modification for individuals classified as obese. In this study, an African American cohort with BMI ≥ 30 kg/m², men were less likely to report having received medical advice (within the past 12 months) for diet and exercise as compared with women; however, those participants who had diabetes (and who were obese; 23.2% males/25.1% females) were advised regardless of gender.

Several large randomized control studies in the 1990s, including the Diabetes Prevention Program (DPP; Knowler et al., 2002) and the Finish Diabetes Prevention Study (DPS; Lindström et al., 2003), furnished evidence that persons at risk for cardiovascular disease improved health outcomes by following diet and physical activity recommendations. The WHO includes diet and exercise as treatment for cardiovascular diseases (WHO, 2011). Yet despite the evidenced-based knowledge for cardiovascular disease prevention, several studies found the overall rate of medical advice reported by patients for diet and exercise to be <10% (Duaso & Cheung, 2002; Windak, Gryglewska, Tomasik, Narkiewicz, & Grodzicki, 2009). Arfken and Houston (1996) found approximately half of obese inner-city African American adults surveyed reported receiving medical advice to reduce fats. These results are consistent with several more recent studies that found 40% to 50% of obese populations did not receive advice for diet and exercise (Ha et al., 2011 and references therein; Ko et al., 2008). Undertreatment for obesity may be that health care providers are not conceptualizing it as a disease (Bardia et al., 2007). Data from medical examinations performed over the course of a year in a primary care facility indicated that only 20% of persons with BMI in the obese range were diagnosed and that those diagnosed were twice as likely to have a treatment plan as compared with those cases not documented (Bardia et al., 2007). This trend of underdiagnosis was present in a nationally represented sample more than 10 years ago (Stafford, Farhat, Misra, & Schoenfeld, 2000), despite the fact that obesity is a billable disease for Medicare coverage (Bardia et al., 2007). Minority status was not associated with communication for individuals with diabetes (Piette, Schillinger, Potter, & Heisler, 2003). Men are among the groups of obese individual that are less likely to receive diagnosis of obesity (Bardia et al., 2007) or medical advice for diet and exercise (Ha et al., 2011).

Understanding and addressing the social determinants, particularly by gender and race, that influence adherence to medical advice is an important public health concern. Even though the participants who reported being given dietary and physical activity advice were more likely to report following the corresponding recommendations, males were less likely to report reducing fat or calories. Since receiving medical advice has been associated with following recommendations, it follows that habitual health care utilization is a precursor for adherence to medical recommendations. Seeking health care is uncommon for African American males (Griffith et al., 2007); however, spouses and family members may encourage and facilitate their visiting a physician (Griffith et al., 2011). Another factor that may prompt African American men to seek medical help is being diagnosed with a chronic disease. Griffith et al. (2011) reported African American men delay seeking medical services until their illness interfered with their personal or social life functioning.

Although for this study, obese African American men were almost 3 times less likely (odds ratio [OR] = 0.36 [0.19, 0.69], p = .005) than obese African American women to report that they were currently reducing fat or calories, having diabetes changed the relationship. Male participants with diabetes were 5 times more likely (OR = 5.10 [2.19, 11.9], p = .001) to report currently reducing fat or calories compared with female participants with diabetes. In summation, those participants given medical advice were more likely to report performing recommended behaviors in diet and physical activity. African American men with diabetes were more likely to report currently making the recommended dietary change than African American women with diabetes; however, there was no difference between genders or diabetes status for following physical activity recommendations.

The enablers and barriers for diabetes care may differ by gender for African Americans. African American women with type 2 diabetes were found to have caregiving responsibilities and feelings of tiredness and psychological stress that interfered with their self-care in a qualitative analysis (Samuel-Hodge et al., 2000). Although there are several studies that examined health behaviors in African Americans, studies specific to African American men with diabetes are scarce. Social determinants that explain whether African Americans adhere to medical advice have included perceived positive social support from spouses, friends, and health care providers in both genders (Chlebowy, Hood, & LaJoie, 2010; Tang, Brown, Funnell, & Anderson, 2008) and in men (Liburd, Namageyo-Funa, & Jack, 2007). Perceived severity of diabetes was associated with a family history of diabetes for African Americans at risk for diabetes (Omolafe, Mouttapa, McMahn, & Tanjasiri, 2010). Susceptibility to diabetes complications (such as cardiovascular and neurological diseases) for African Americans with diabetes has been associated with seeking medical help and following medical recommendations (Chlebowy et al., 2010 and references therein).

There was twice the likelihood of increasing physical activity for participants reporting receiving this advice for both genders. Encouragement to increase physical activity by health care professionals may be necessary to combat social norms. Gender roles responsibilities have been considered barriers for physical activity for women in numerous studies and in several studies of African American men (Griffith et al., 2011 and references therein). Prioritizing work and family and community commitment over health may be considered a cultural norm for African American men (Griffith et al., 2011).

Limitations

Although BMI was measured, it is only a proxy measurement of percentage body fat. Since muscle weighs more than fat, persons with a higher muscle mass may have lower percentage body fat and BMI cutoffs for the obesity category may not be applicable to these persons (athletes and persons with a genetic predisposition to higher percentage muscle mass than average). Therefore, percentage body fat and muscle mass may alter the relationship between BMI and obesity (CDC, 2011; National Obesity Observatory, 2009). There are multiple confounders in the measurement of medical advice for this study, as well. Medical advice was self-reported, may be limited by recall bias, and was likely to be underestimated (Windak et al., 2009). Not remembering receiving advice may attest to the quality of the patient–provider relationship. Investigation into patient–provider communication was lacking in this study. Even if medical advice for diet and physical activity was received, the information may be processed and remembered differently by gender within and across ethnicities. The extent of the dialogue for reducing fat and increasing exercise was not available in this quantitative study. Although the majority of participants reported having health care insurance (>70%), their utilization was not assessed and according to the literature previously discussed may have been lower for men than women.

Recommendations

Physicians’ normative beliefs concerning race and gender may influence their diagnosis and treatment of obesity (Leverence et al., 2007). In order to gain an understanding of how to provide African American men with effective health care, further in-depth research is needed. Recommendations for research include longitudinal, qualitative studies, designed to examine how normative beliefs of the patient–provider dyads effect medical advice given and adherence to the recommendations. These studies are of particular importance because of conflict in the present research concerning the race- gender- and health care provider type-concord and patient outcomes. Moreover, there are limited studies of African American males, patient–provider race concordance and their effect on health behavior.

Effective patient–provider communication may be a factor of ethnic similarities (race concordance); however, within-race gender differences and race concordance have received little attention. With respect to patient–provider communication, several studies have investigated the effect of same versus different ethnicities in the patient–provider dyad. There are conflicting findings concerning physician and patients of the same race with the effectiveness and quality of medical advice. While some studies have found same-race/ethnicity dyads to have more effective communication, others reported no statistically significant differences between same- and mixed-ethnicity dyads. Meghani et al. (2009) reviewed patient–provider, race concordance and reported that of the 27 studies approximately one-third were Caucasian, one-third were African American, and 13% were Hispanic. The authors found patient provider race-concordance was associated with positive health outcomes for minorities in nine studies, while eight studies found no association of race-concordance with the outcomes studied and 10 presented mixed findings.

Furthermore, patient–provider race concordance and health behaviors may be different for African American men as compared with African American women. That is, racial concordance may mediate behavioral change for one gender but not for the other in African American population; albeit, there are no studies to date that investigated these associations. A study examining social concordance (same race, gender, similar age, and education) of African American and Caucasian patients with their physicians found low social concordance to be associated with dissatisfaction with medical care and lower self-rated health (Thornton et al., 2011). Moreover, the investigators reported Caucasian patients to be significantly more likely to be in high social concordance as compared with African American patients (Thornton et al., 2011).

Gender and health professional type (dietitian, nurse practitioner, or physician) may also affect the patients’ level of trust in the information and guidance received. Although there are no studies to date that explore African American men’s gender preference for their health care professional, a mixed methods, cross-sectional, investigation of urban African American women, aged 45 to 93 years, found participants were less likely to prefer female physicians when they were more educated, took an active role in their care, and felt they were respected by supporting staff at the physician’s office (Casciotti & Klassen, 2011).

Utilization of care by gender and disease state is another area recommended for future research since the literature is in discord. Several studies found frequency and continuity of care was associated with improvement of glycemic control for patients with type 2 diabetes in a cohort of African Americans (El-Kebbi et al., 2003) and in a primarily Mexican American cohort (Parchman, Pugh, Noel, & Larme, 2002). Similarly, Piette, Schillinger, Potter, and Heisler (2003) reported a higher probability of patients who reported good communication with their physicians and exercise and dietary adherence using validated questionnaires in a multicultural cohort from three different health care systems. Conversely, Gulliford, Naithani, and Morgan (2007) reported the patient’s satisfaction of their continuity of care for type 2 diabetes was not associated with improvements in glycemic control (measured by glycated hemoglobin A1c) with a reliable, validated questionnaire.

Our results are consistent with those of Ha et al. (2011), who showed that obese men were less likely to receive medical advice for diet and exercise than women. Perhaps these results are related to the findings of Bardia et al. (2007) who found obese men were less likely to be medically diagnosed as “obese” as compared with women. Physicians who underdiagnose obesity in men may be affected by underlying norms of masculinity, in which men are invincible and have the ability to lose weight at will.

The finding that African Americans, regardless of gender, who were reported receiving medical advice on diet and physical activity, were more likely to perform the corresponding behavior attests to the need for more effective patient–provider communication. Using focus groups, Griffith et al. (2011) indicated a common norm expressed by urban middle-aged African American men was that “physicians told them to make changes, but did not explain how to make them.” Their work and the evidence in the literature indicating the health benefits of family encouragement for African American men, together with the results of this report, support the need for intervention studies that compare the standard client-centered physician approach with an enhanced client-centered approach that involves a health care team, family, and community support. Moreover, these findings emphasize the continued need to characterize the role of the health care professional in the diagnosis and treatment of obesity.

There are several confounders of this study when considering gender differences in medical advice received. Medical advice was by self-report and may differ from actual advice received. Therefore, the content cannot be separated from the quality of advice given. Patient–provider communication is a confounder in this study. For participants to report receiving medical advice in the past year, that advice would have to be delivered so that the person would process and remember receiving it as it was intended. Effective delivery of the intended message would depend, in part, on the linguistic and cultural competency of the health care provider (Goode & Jones, 2009).

Conclusion

For this study, obese males were less likely to report having received medical advice to modify their diet and increase exercise. Participants who received advice were more likely to perform the recommended behavior. Since the advice received was by self-report, it was not possible to determine if the message was not given or if it was ineffectively delivered. Culturally competent, standard care for obesity, independent of gender and race, is imperative. These findings may suggest that educational programs aimed at reducing race, gender, and body size biases of health professionals could help eliminate health disparities in African American men.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Agency for Healthcare Research and Quality. (2011). National Healthcare Quality Report, 2010 (Medical expenditure panel survey, 2002-2007). Rockville, MD: Author. Retrieved from http://www.ahrq.gov/qual/nhqr10/Chap2c.htm

American Diabetes Association. (2011). Standards of medical care in diabetes—2011. Diabetes Care, 34(Suppl. 1), S11-S61.

Anderson

Peterson

C. B.

Fletcher

Mitchell

J. E.

Thuras

Crow

S. J.

(2001). Weight loss and gender: An examination of physician attitudes, Obesity Research, 9, 257-263.

Arfken

Houston

C. A.

(1996). Obesity in inner-city African Americans. Ethnicity & Health, 1, 317-326.

Bach

P. B.

Hoangmai

Schrag

Tate

R. C.

Hargraves

J. L.

(2004). Primary care physicians who treat Blacks and Whites. New England Journal of Medicine, 351, 575-584.

Bardia

Holtan

S. G.

Slezak

J. M.

Thompson

W. G.

(2007). Diagnosis of obesity by primary care physicians and impact on obesity management. Mayo Clinic Proceedings, 82, 927-932.

Betancourt

J. R.

Green

A. R.

Carrillo

J. E.

Ananeh-Firempong

(2003). Defining cultural competence: A practical framework for addressing racial/ethnic disparities in health and health care. Public Health Reports, 118, 293-302.

Casciotti

D. M.

Klassen

A. C.

(2011). Factors associated with female provider preference among African American women, and implications for breast cancer screening. Health Care for Women International, 32, 581-598

Centers for Disease Control and Prevention. (2010a). Health United States, 2009. Table 72: Age-adjusted percentage of overweight persons 20 years of age and over who are obese, 2005-2008. Retrieved from http://www.cdc.gov/nchs/data/hus/hus09.pdf

10.

Centers for Disease Control and Prevention. (2010b). Health United States, 2009. Table 51: Age-adjusted percentages of physician-diagnosed diabetes among persons 20 years of age and over, 2003-2006. Retrieved from http://www.cdc.gov/nchs/data/hus/hus09.pdf

11.

Centers for Disease Control and Prevention. (2011). Body mass index: Considerations for practitioners. Retrieved from http://www.cdc.gov/obesity/downloads/BMIforPactitioners.pdf

12.

Chlebowy

D. O.

Hood

LaJoie

A. S.

(2010). Facilitators and barriers to self-management of type 2 diabetes among urban African American adults: Focus group findings. Diabetes Educator, 36, 897-905.

13.

Cross

T. L.

Bazron

B. J.

Dennis

K. W.

Isaacs

M. R.

(1989). Towards a culturally competent system of care: A monograph on effective services for minority children who are severely emotionally disturbed. Washington, DC: CASSP Technical Assistance Center, Georgetown University Child Development Center.

14.

Deakin

T. A.

Cade

Williams

Greenwood

(2006). Structured patient education: The diabetes X-pert Programme makes a difference. Diabetic Medicine, 23, 944-954.

15.

Duaso

M. J.

Cheung

(2002). Health promotion and lifestyle advice in a general practice: What do patients think? Journal of Advanced Nursing, 39, 472-479.

16.

Eakin

Brown

Schofield

Mummery

Reeves

(2007). General practitioner advice on physical activity: Who gets it? American Journal of Health Promotion, 21, 225-228.

17.

El-Kebbi

I. M.

Cook

C. B.

Ziemer

D. C.

Miller

C. D.

Gallina

D. L.

Phillips

L. S.

(2003). Association of younger age with poorer glycemic control and obesity in urban African Americans with type 2 diabetes. Archives of Internal Medicine, 163, 69-75.

18.

Fatone

Jandorf

(2009). Predictors of cervical cancer screening among urban African Americans and Latinas. American Journal of Health Behavior, 33, 416-424.

19.

Finkelstein

E. A.

Trogdon

J. G.

Cohen

J. W.

Dietz

(2009). Annual medical spending attributable to obesity: Payer- and service-specific estimates. Health Affairs, 28, w822-w831.

20.

Flegal

K. M.

Carroll

M. D.

Ogden

C. L.

Curtin

L. R.

(2010). Prevalence and trends in Obesity among US adults, 1999-2008. Journal of the American Medical Association, 303, 235-241.

21.

Flegal

K. M.

Graubard

B. I.

Williamson

D. R.

Gail

M. H.

(2005). Excess deaths associated with underweight, overweight, and obesity. Journal of the American Medical Association, 293, 1861-1867.

22.

Goode

Jones

(2009). Definition of linguistic competence. Washington, DC: National Center for Cultural Competence, Georgetown University Center for Child and Human Development. Retrieved from http://gucchd.georgetowm.edu/nccc

23.

Griffith

D. M.

Allen

J. O.

Gunter

(2011). Social and cultural factors influence African American men’s medical help seeking. Research on Social Work Practice, 21, 337-347.

24.

Griffith

D. M.

Mason

M. A.

Rodela

Matthews

D. D.

Tran

Royster

. . . Eng

(2007). A structural approach to examining prostate cancer risk for rural southern African American men. Journal of Health Care for the Poor and Underserved, 18, 73-101.

25.

Gulliford

M. C.

Naithani

Morgan

(2007). Continuity of care and intermediate outcomes of type 2 diabetes mellitus. Family Practice, 24, 245-251.

26.

Nguyen

H. T.

Markides

K. S.

Winkleby

M. A.

(2011). Physician advice on exercise and diet in a U.S. sample of obese Mexican-American adults. American Journal of Health Promotion, 25, 402-409.

27.

Haslam

Sherratt

Holdsworth

Beardsworth

Keil

Goode

(2000). Social factors associated with self-reported dietary change. Journal of Nutrition Education, 32, 296-303.

28.

Hinrichs

Moschny

Klaaßen-Mielke

Trampisch

Thiem

Platen

(2011). General practitioner advice on physical activity: Analyses in a cohort of older primary health care patients (getABI). BMC Family Practice, 12, 26. doi:10.1186/1471-2296-12-2610.1186/1471-2296-12-26

29.

Knowler

W. C.

Barrett-Connor

Fowler

S. E.

Hamman

R. F.

Lachin

J. M.

Walker

E. A.

Nathan

D. M.

(2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine, 346, 393-403.

30.

M. Y.

Brown

D. R.

Galuska

D. A.

Zhang

Blanck

H. M.

Ainsworth

B. E.

(2008). Weight loss advice U.A. obese adults receive from health care professionals. Preventive Medicine, 46, 587-592.

31.

Kochanek

K. D.

Murphy

S. L.

Miniño

A. M.

Kung

H-C.

(2011). Deaths: Preliminary data for 2009. National Vital Statistics Reports, 58(4). Hyattsville, MD: National Center for Health Statistics. Retrieved from http://www.cdc.gov/nchs/products/nvsr.htm#vol58

32.

Leverence

Williams

Sussman

Crabtree

(2007). Obesity counseling and guidelines in primary care a qualitative study. American Journal of Preventive Medicine, 32, 334-339.

33.

Liburd

L. C.

Namageyo-Funa

Jack

Jr. (2007). Understanding “masculinity” and the challenges of managing type-2 diabetes among African-American men. Journal of the National Medical Association, 99, 550-558.

34.

Lindström

Louheranta

Mannelin

Rastas

Salminen

Erikkson

. . . Tuomilehto

(2003). The Finnish Diabetes Prevention Study (DPS). Diabetes Care, 26, 3230-3236.

35.

Loureiro

M. L.

Nayga

R. M.

Jr. (2006). Obesity, weight loss, and physician’s advice. Social Science & Medicine, 62, 2458-2468.

36.

Urizar

G. G.

Jr. Alehegn

Stafford

R. S.

(2004). Diet and physical activity counseling during ambulatory care visits in the United States. Preventive Medicine, 39, 815-822.

37.

McCann

D. P.

Blossom

(1990). The physician as a patient educator: From theory to practice. Western Journal of Medicine, 153, 44-49.

38.

Meghani

S. H.

Brooks

J. M.

Gipson-Jones

Waite

Whitfield-Harris

Deatrick

J. A.

(2009). Patient- provider race-concordance: does it matter in improving minority patients’ health outcomes? Ethnicity & Health, 14, 107-130.

39.

Moonesinghe

Zhu

Truman

B. I.

(2011). Health insurance coverage—United States, 2004 and 2008. Morbidity and Mortality Weekly Report Surveillance Summaries, 60(Suppl.), 35-37.

40.

National Health and Nutrition Examination Survey. (2011a). NHANES 2007-2008. http://www.cdc.gov/nchs/nhanes/nhanes2007-2008/nhanes07_08.htm

41.

National Health and Nutrition Examination Survey. (2011b). Questionnaires, datasets, and related documentation. http://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm

42.

National Obesity Observatory. (2009). Body mass index as a measure of obesity. Retrieved from http://www.noo.org.uk/publications/719/Body_Mass_Index_as_a_measure_of_obesity

43.

Nelson

(2002). Unequal treatment: Confronting racial and ethnic disparities in health care. Journal of the National Medical Association, 94, 666-668.

44.

Omolafe

Mouttapa

McMahan

Tanjasiri

S. P.

(2010). We are family: Family history of diabetes among African Americans and its association to perceived severity, knowledge of risk factors, and physical activity levels. Californian Journal of Health Promotion, 8, 88-97.

45.

Parchman

M. L.

Pugh

J. A.

Noel

P. H.

Larme

A. C.

(2002). Continuity of care, self-management behaviors, and glucose control in patients with type 2 diabetes. Medical Care, 40, 137-144.

46.

Peyrot

Rubin

R. R.

Lauritzen

Snoek

F. J.

Matthews

D. R.

Skovlund

S. E.

(2005). Psychosocial problems and barriers to improved diabetes management: Results of the Cross-National Diabetes Attitudes, Wishes and Needs (DAWN) Study. Diabetes Medicine, 22, 1379-1385.

47.

Phili-Tsimikas

Walker

Rivard

Talavera

Reimann

J. O. F.

Salmon

, . . . Project Dulce. (2004). Improvement in diabetes care of underinsured patients enrolled in Project Dulce: A community-based, culturally appropriate, nurse case management and peer education diabetes care model. Diabetes Care, 27, 110-115.

48.

Piette

J. D.

Schillinger

Potter

M. B.

Heisler

(2003). Dimensions of patient-provider communication and diabetes self-care in an ethnically diverse population. Journal of General Internal Medicine, 10, 624-633.

49.

Roter

Lipkin

Jr. Korsgaard

(1991). Sex differences in patients’ and physicians’ communication during primary care medical visits. Medical Care, 29, 1083-1093.

50.

Safran

E. G.

Taira

D. A.

Rogers

W. H.

Kosinski

Ware

J. E.

Tarlov

A. R.

(1998). Linking primary care performance to outcomes of care. Journal of Family Practice, 47, 213-220.

51.

Samuel-Hodge

C. D.

Headen

S. W.

Skelly

A. H.

Ingram

A. F.

Keyserling

T. C.

Jackson

E. J.

. . . Elay

T. A.

(2000). Influences on day-to-day self management of type 2 diabetes among African-American women: spirituality, the multi-caregiver role, and other social context factors. Diabetes Care, 23, 928-933.

52.

Stafford

R. S.

Farhat

J. H.

Misra

Schoenfeld

D. A.

(2000). National patterns of physician activities related to obesity management. Archives of Family Medicine, 9, 631-638.

53.

Tang

T. S.

Brown

M. B.

Funnell

M. M.

Anderson

R. M.

(2008). Social support, quality of life, and self-care behaviors among African Americans with type 2 diabetes. Diabetes Educator, 34, 266-276.

54.

Tang

T. S.

Funnell

M. M.

Brown

M. B.

Kurlander (2010). Self-management support in “real-world” settings: An empowerment-based intervention. Patient Education and Counseling, 79, 178-184.

55.

Tang

T. S.

Gilliard

M. L.

Funnell

M. M.

Nwankwo

Parker

Spurlock

Anderson

R. M.

(2005). Developing a new generation of ongoing diabetes self management support interventions: A preliminary report. Diabetes Educator, 31, 91-97.

56.

Thornton

R. L. J.

Powe

N. R.

Roter

Cooper

L. A.

(2011). Patient-physician social concordance, medical visit communication and patients’ perceptions of health care quality. Patient Education and Counseling, 85, e201-e208.

57.

Truswell

S. A.

(2000). Family physicians and patients: is effective nutrition interaction possible? American Journal of Clinical Nutrition, 71, 6-12.

58.

U.S. Department of Health and Human Services. (2001). The Surgeon General’s call to action to prevent and decrease overweight and obesity. Rockville, MD: Author.

59.

U.S. Department of Health and Human Services. (2010). The Surgeon General’s vision for a healthy and fit nation. Rockville, MD: Author.

60.

Windak

Gryglewska

Tomasik

Narkiewicz

Grodzicki

(2009). Competence of general practitioners in giving advice about changes in lifestyle to hypertensive patients. Medical Decision Making, 29, 217-223.

61.

World Health Organization. (2011). Cardiovascular diseases (Fact sheet no. 317). Retrieved from http://www.who.int/mediacentre/factsheets/fs317/en/index.html

62.

World Health Organization. (2012). The social determinants of health. Retrieved from http://www.who.int/social_determinants/en/