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. 2021 Apr 7;16(4):e0249188. doi: 10.1371/journal.pone.0249188

Prevalence and predictors of obesity-related cancers among racial/ethnic groups with metabolic syndrome

Shanada Monestime 1,*, Bettina Beech 2, Dulcie Kermah 3, Keith Norris 4
Editor: Frank T Spradley5
PMCID: PMC8026066  PMID: 33826671

Abstract

Background

Obesity-related cancer (ORC) is associated with higher amounts of body fat, which could increase the risk of developing cardiovascular disease (CVD). A significant factor associated with CVD is metabolic syndrome (MetS), and MetS prevalence differs by race/ethnicity. The purpose of this study was to compare the prevalence and predictors of ORCs by race/ethnicity among adults (>18) with MetS.

Methods

This was a retrospective, cross-sectional study using data from the 1999–2014 National Health and Nutrition Examination Survey (NHANES). A chi-square test was performed to determine differences in ORC prevalence between non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic participants with MetS. A multivariate logistic regression was used to evaluate predictors (race, sex, income, insurance, education, marital status, and smoking status) of ORC among adults with MetS.

Results

Of the 1,554 adults, the prevalence of ORC was 30.6% among NHWs, 51.3% in NHBs, and 54.1% in Hispanics (p = <0.001). Females were 6.27 times more likely to have an ORC compared to males (95% CI = 4.95–14.11). Compared to NHWs, NHBs were 2.1 times more likely to have an ORC (95% CI = 1.40–3.38); and Hispanics were 2.5 times more likely (95% CI = 1.39–4.77). For every 1-year unit increase in age, the odds of ORC increased by 3% (95% CI = 1.00–1.05).

Conclusions

Among NHANES participants with MetS, the prevalence of ORCs was significantly higher in NHBs and Hispanics, females, and older adults with MetS. Future studies, by race/ethnicity, are warranted on mortality risk of persons with MetS and ORC.

Introduction

Obesity-related cancers (ORCs) account for 40% of all cancer diagnoses in the United States and are associated with higher health expenditures compared to non-ORCs [1,2]. ORCs are hypothesized to have biological properties that are related to poor prognosis [3]. These types of cancers are associated with higher body mass index (BMI ≥25 kg/m2) and include meningioma, bladder, esophageal, kidney, endometrial, ovarian, thyroid, liver, gallbladder, stomach, pancreatic, colorectal, and certain blood cancers [1,47]. It is important to note that not all adults who have an ORC are overweight or obese. However, among adults with cancer and obesity, an association exists with a reduced likelihood of undergoing cancer screening, difficulty in detecting cancer during a physical exam, and receiving suboptimal doses of chemotherapy [3]. Also, numerous sequelae are associated with having ORCs such as having an increased risk of type 2 diabetes, hypertension, coronary heart disease, or a combination of these. A concern exists that these risk factors can lead to cardiovascular disease (CVD) [8], which remains the leading cause of death in cancer survivors [9].

Risk factors for cardiovascular disease tend to cluster into interrelated groups of conditions commonly known as metabolic syndrome (MetS), which has been associated with an increased risk of CVD in adults with cancer [10]. MetS is defined by having at least three of the following: abdominal obesity, diabetes, hypertension, hypertriglyceridemia, or low levels of high-density lipoprotein (HDL). Lifestyle interventions, including increasing physical activity and reducing excessive caloric intake, are widely accepted as safe and effective treatments for MetS [11]. Furthermore, excessive caloric intake from frequent consumption of soft drinks has been consistently correlated with a higher waist circumference and a modest increase in risk for developing an ORC among adults [12]. In addition, the risk of breast cancer, which is the most common ORC, was lower among the most physically active women compared to the least active women in the majority of studies evaluated in a systematic review [13]. The high prevalence of sedentary lifestyle and associated weight gain seen in the United States may be a contributing factor to the high rates of MetS and cardiovascular morbidity observed in cancer survivors [11]. Therefore, a critical need exists to understand ORC as it relates to a diagnosis of MetS.

Previous studies have identified the prevalence of ORC to be higher in non-Hispanic Blacks and Hispanics compared with non-Hispanic Whites [1,2]. However, prior studies did not control for sociodemographic and lifestyle factors that can differ across race/ethnicity and that may provide further insights on why select groups may be at risk for developing CVD. Therefore, the primary objective of this study was to compare, by race/ethnicity, the prevalence of ORCs among a nationally representative sample of adults with MetS. The secondary objective was to identify predictors associated with adults who have MetS concurrently with an ORC.

Methods

Study design

Data were obtained from the 1999–2014 National Health and Nutrition Examination Survey (NHANES), a series of cross-sectional surveys of adults in U.S. households. Home interviews were conducted to collect self-reported information, including, but not limited to, demographic data, socioeconomic data, and cancer diagnosis, followed by an extensive physical examination and blood collection at a mobile examination center [14,15]. The survey uses a complex, multistage probability design to provide a nationally representative sample of the U.S. civilian noninstitutionalized population and allows for a high level of generalizability to the nation’s population. Further details of the NHANES survey design, questionnaires, and examination methods are described elsewhere [16]. The present study was not reviewed by the Institutional Review Board as the data analyzed are de-identified and publicly accessible.

Study population

Adult NHANES participants were included in the analytic sample if they self-reported as non-Hispanic White, non-Hispanic Black, or Hispanic; were greater than 20 years old; and were diagnosed with comorbid MetS and cancer. Pregnant women were excluded because of increased waist circumference and potential pregnancy-related metabolic changes. Respondents who self-identified as “Mexican American” and “other self-identified Hispanics” were grouped as Hispanics. All other non-Hispanic participants were categorized based on their self-reported race.

Adults categorized as having MetS (at least three of the following: hypertension, diabetes, abdominal obesity, hypertriglyceridemia, or low levels of HDL) were identified using related NHANES questions and laboratory values defined by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) guidelines. Hypertension was defined by a measurement of 130/85 mmHg or greater and/or a positive response to the question, “Are you now taking prescribed medicine (for blood pressure)?” Diabetes mellitus was defined by a fasting blood sugar over 100 mg/dL and/or a positive response to the question, “Are you now taking diabetic pills to lower blood sugar?” or “Are you taking insulin now?” Abdominal obesity was defined by a waist circumference over 40 inches (men) or 35 inches (women). Hypertriglyceridemia was defined as a fasting triglyceride level over 150 mg/dL, and low HDL cholesterol levels were defined by a fasting HDL cholesterol level less than 40 mg/dL (men) or 50 mg/dL (women).

Among participants with MetS, we identified those with one or more cancers. We determined whether adults had an ORC compared to a non-ORC based on their response to the following question, “Have you ever been told by a doctor or other health professional that you had cancer or a malignancy of any kind?” Presence of an ORC was determined if the respondent had a diagnosis of at least one the following cancers: brain, bladder, esophageal, kidney, endometrial, ovarian, thyroid, breast, liver, gallbladder, stomach, pancreatic, or colorectal [4,5]. All other cancers were defined as non-ORCs (bone, blood, cervical, head and neck, leukemia, liver, lung, lymphoma, melanoma, nervous system, prostate, rectum, skin cancer (non-melanoma), testicular, and other cancers). An affirmative response to having cancer was followed by an opportunity to specify up to three different cancer diagnoses. If one of three cancers was obesity related, the survey participant was categorized as having an ORC, even if the other two cancers were non–obesity related. Respondents who had non-ORCs were defined by not having a prior or current diagnosis of an ORC.

Study variables

Covariates included sociodemographic factors, insurance status, and smoking status. Sociodemographic factors included five variables. Age was measured as a continuous variable, and sex was coded as a dichotomous variable that indicated whether a participant was female or male. Education status was stratified by whether participants completed less than high school, a high school diploma/general education diploma (GED) or equivalent, or some college or above. Income was determined by the family’s total annual income of either less than $35,000; $35,000 to $74,999; or $75,000 and above. Marital status was stratified by being a widow, divorced, separated, never married, married, or living with a partner. Insurance status was coded as a dichotomous variable, indicating whether a participant was insured. Lastly, smoking status was stratified by the participant either smoking every day, some days, or not at all.

Statistical analysis

All statistical analyses were conducted using SAS 9.4. Statistical significance was assessed with two-tailed tests and α = 0.05. A chi-square test was performed to determine differences in ORC prevalence among non-Hispanic Whites, non-Hispanic Blacks, and Hispanics diagnosed as having both MetS and cancer. A multivariable logistic regression was used to evaluate possible predictors (race, sex, income, insurance, education, marital status, and smoking status) of ORC among adults with MetS. Data from the regression model were reported as the odds ratio (OR), 95% confidence interval (CI), and associated p-value for the specific characteristic. We calculated the mean and SD for continuous variables. For categorical variables, we obtained the frequencies.

Results

Patient characteristics

Among 1,554 adults diagnosed with MetS, a higher prevalence of non-ORCs (n = 974, 67%) existed compared with ORCs (n = 580, 33%). Among the 580 adults with ORC, the mean age was 64.2 years (SE ± 0.76), and most were female (n = 448, 81.6%), non-Hispanic White (n = 376, 82.9%), married (n = 286, 57.4%), and non-smokers (n = 205, 71.3%). Nearly half of the study participants had some college education or above (n = 229, 48.1%), nearly a third had income less than $35,000 (n = 177, 32%), and most had some form of health insurance (n = 544, 95.3%). The top five ORCs in this sample were breast, colorectal, uterine, bladder, and ovarian cancer (Fig 1). For adults with non-ORCs, the mean age was 67.5 years (SE ± 0.46), and most of the adults were male (n = 634, 60.1%), non-Hispanic White (n = 759, 92.38%), married (n = 623, 67.2%), non-smokers (n = 456, 72.4%), had some college-education or above (n = 497, 58.2%), and had health insurance (n = 917, 93.4%). Annual income was equally distributed across categories of less than less than $35,000; $35,000 to $74,999; or $75,000 and above. All baseline characteristics differed between obese and non-obese groups with the exception of insurance status (p = 0.29) and smoking status (p = 0.5; Table 1).

Fig 1. Prevalence of specific obesity-related cancers.

Fig 1

The most common were breast (14.6%), colorectal (6.6%), and uterine (4.3%) cancer.

Table 1. Baseline characteristics of comorbid metabolic syndrome and cancer, NHANES 1999–2014.

Characteristics All (N = 1554) Diagnosed with an ORC p-value
Yes, % (N = 580) No, % (974)
Age 64.2 (SE ± 0.76) 67.5 (SE ± 0.46) <0.001
Sex <0.001
    Female 788 448 (81.6) 340 (39.9)
    Male 766 132 (18.4) 634 (60.1)
Race <0.001
    Non-Hispanic Black 239 112 (9.84) 127 (4.6%)
    Hispanic 189 101 (7.2) 88 (3.01))
    Non-Hispanic White 1126 367 (82.9) 759 (92.38)
Marital status 0.01
    Married 909 286 (57.4) 623 (67.21)
    Divorce 170 73 (12.9) 97 (11.1)
    Living with partner 37 10 (1.2) 27 (2.8)
    Never married 63 28 (4) 35 (3.8)
    Separated 38 12 (1.86) 26 (1.79)
    Widowed 326 166 (45.5) 160 (54.5)
Education <0.001
    Less than high school 450 210 (25.3) 240 (16.5)
    High school/GED (ref) 376 141 (26.6) 235 (25.3)
    Some college and above 726 229 (48.1) 497 (58.2)
Annual Income 0.01
    <$35,000 404 177 (32) 227 (22.7)
    $35,000–74,999 264 105 (21.7) 159 (21.9)
    $75,000+ 168 41 (14.2) 127 (22.5)
    Missing 675 240 (32.1) 435 (32.9)
Health Insurance 0.29
    No 87 36 (4.7) 51 (6.6)
    Yes 1461 544 (95.3) 917 (93.4)
Smoker 0.5
    Every day 188 59 (24.3) 129 (25)
    Some days 32 15 (4.4) 17 (2.5)
    Not at all 661 205 (71.3) 456 (72.4)

Weighted percentages were calculated.

Weighted prevalence of obesity-related cancer by race/ethnicity

Of the adults with comorbid MetS and cancer, 239 (6.32%) were non-Hispanic Blacks, 189 (4.40%) were Hispanics, and 1126 (89.27%) were non-Hispanic Whites. The prevalence of ORC among non-Hispanic Blacks, Hispanics, and Whites was 51%, 54%, and 31%, respectively (p = <0.001). However, for non-ORCs, the prevalence was higher in non-Hispanic Whites (69%; Fig 2).

Fig 2. Prevalence of obesity-related cancers among NHANES participants with metabolic syndrome, by race and ethnicity.

Fig 2

The prevalence of obesity-related cancers was 31% in non-Hispanic Whites, 51% in non-Hispanic Blacks, and 54% in Hispanics (p = <0.001).

Predictors of obesity-related cancers among adults with comorbid metabolic syndrome and cancer

Of the predictors analyzed using a multivariable logistic regression approach, three of the eight variables were significantly associated with ORC in adults with comorbid MetS and cancer. Females were 6.27 times more likely to have an ORC than males (95% CI = 4.95–14.11; p = <0.0001). For race/ethnicity, non-Hispanic Blacks were 2.1 times more likely to have an ORC than non-Hispanic Whites (95% CI = 1.40–3.38; p = <0.001); and Hispanics were 2.5 times more likely to have an ORC than non-Hispanic Whites (95% CI = 1.39–4.77; p = <0.01). For every 1-year unit increase in age, the odds of ORC increased by 3% (95% CI = 1.00–1.05; p = <0.01). Education, marital status, insurance status, income, and smoking status were not significant predictors of ORC (Table 2).

Table 2. Multivariable logistic regression analysis of obesity-related cancers in adults with metabolic syndrome, National Health and Nutrition Examination Survey 1999–2014.

Independent Variable OR (95% CI) p-value
Age 1.03 (1.0–1.05) <0.01
Sex
    Female 6.27 (3.89–10.12) <0.0001
    Male (ref.) - -
Race
    Non-Hispanic Black 2.1 (1.40–3.38) <0.001
    Hispanic 2.5 (1.39–4.77) <0.01
    Non-Hispanic White (ref.) - -
Marital status
    Married 1.81 (0.96–3.41) 0.06
    Divorce 2.07 (0.92–4.67) 0.07
    Living with partner 0.58 (0.14–2.35) 0.44
    Never married 1.72 (0.45–6.51) 0.41
    Separated 0.69 (0.20–2.31) 0.54
    Widowed (ref.) -
Education
    Less than high school 1.63 (0.97–2.73) 0.07
    High school/GED (ref) -
    Some college and above 1.28 (0.68–2.40) 0.98
Annual Income
    <$35,000 1.15 (0.53–2.48) 0.70
    $35,000–74,999 0.66 (0.29–1.56) 0.35
    Missing 0.66 (0.31–1.42) 0.29
    $75,000+ (ref) - -
Health Insurance
    No 0.44 (0.13–1.54) 0.20
    Yes (ref) - -
Smoker
    Everyday 0.84 (0.25–2.83) 0.81
    Not at all 0.84 (0.26–2.73) 0.81
    Some days (ref) - -

OR = odds ratio. The regression controlled for race, sex, income, insurance, education, marital status, and smoking status.

Discussion

Evidence consistently shows that higher BMI is associated with an increased risk of ORCs [1,1722]. From 1997 to 2014, obesity rates rose significantly among adult cancer survivors compared with rates in the general population [23]. In our study, we identified a higher prevalence of ORCs in both non-Hispanic Black and Hispanic study participants (>50% for each) with MetS compared with non-Hispanic Whites with MetS, who had a prevalence of less than one-third. This higher prevalence remained significant after controlling for multiple demographic, socioeconomic, and medical factors.

Our findings are consistent with a subgroup analysis in a previous study examining data from the 2008–2015 Medical Expenditure Panel Survey, which used estimated annual health expenditures by ORCs and other cancer types while controlling for sociodemographic and clinical characteristics.2 The analysis showed a higher prevalence of ORCs among racial and ethnic minorities (32%–46%) compared with the prevalence among non-Hispanic Whites (25%). Although the overall descriptive analysis identified differences in the prevalence of ORC by race/ethnicity, a regression model was not performed to identify groups at higher risk for developing ORC in individuals with MetS [2]. Similarly, Steele et al. assessed data from several cancer registries by sex, age, race/ethnicity, and U.S. region. Incidence rates for overweight and ORC were higher among non-Hispanic Blacks and non-Hispanic Whites compared with the rates for Hispanics, American Indians/Alaska Natives, and Asians/Pacific Islanders, but again did not conduct a regression model to identify groups at higher risk for developing ORC in individuals with MetS.

Our study identified the increased prevalence of ORC in individuals from the Hispanic and African American communities with MetS. This association warrants increased attention to considering cardiovascular prevention and early intervention strategies in these high risk groups. The explanations for racial/ethnic differences seen in our study and previous studies are not clear. Race and ethnicity are social constructs that mainly reflect inequities due to the longstanding and persisting role of structural racism on health [24]. These inequities could account for the increased cardiovascular risk as well as a lifetime of social and economic stressors that may lead to weathering and be expressed as increased allostatic load, inflammation, epigenetic changes, and more [25,26], that may interact with ORC.

Although limited data are available on the direct effects of having an ORC compared to a non-ORC, it has been demonstrated that adults with an ORC had approximately 2.1 times higher excess health care expenditures than those with a non-ORC [2]. Therefore, prevention and early intervention strategies could reduce not only the individual/family burden but the economic burden within the health care system.

Findings from our study also demonstrated gender as a significant factor associated with ORC in our cohort with MetS. Similar to prior studies [2,27], we found that women were more likely than males to be diagnosed with an ORC, potentially due to breast cancer being the most prevalent ORC within this study. The association between BMI and ORC may differ by sex, as Chadid and colleagues [28] reported that ORC risk among women increased with a BMI of at least 26 kg/m2 but at least 28 kg/m2 for men. Therefore, further studies analyzing ORC risk factors by sex while considering BMI are imperative for future studies. We also identified that as age increased, adults with MetS were more likely to have an ORC. Our findings support those of Steele and collegues in demonstrating that incidence rates for co-occurring overweight and ORC were higher among older persons (aged ≥50 years) than among younger persons, and two-thirds of cases occurred among persons aged 50 to 74 years [1]. By contrast, Hong et al. [2] reported patients with ORC were more likely to be younger, but their analysis was conducted on cancer registry data unlike the study by Steele et al. and our study which analyzed the general population samples.

This study had several limitations. The first limitation was the use of self-reported data on ORC as well as race and ethnicity which could lead to potential bias or inaccurate information. A second limitation was that our study explored all cancers, so we were unable to identify whether a specific cancer dominated our findings. Our approach provided us with general information. Future studies can address more specific information. A third limitation was our inability to control for additional factors such as access to care; however, over 90% of our cohort had health insurance. A fourth limitation was that we could not capture all ORCs, such as multiple myeloma and meningioma, due to the broad category of blood cancers or brain cancer. However, numbers for brain and blood cancers were extremely low within the dataset; therefore, we could predict this would not impact our current findings. These limitations were balanced by the many strengths of our study, including a nationally represented cohort undergoing a rigorous health analysis in a structured manner and the ability to control for demographic, socioeconomic, and clinical data. Thus, our finding strengthens the current literature on race/ethnicity differences in ORC prevalence, especially in a high-risk cohort with MetS.

Future directions and interventions could focus on the impact of MetS treatment (e.g., weight loss education, diet, and exercise) on ORC, as well as to examine if these associations are driven by individual components of MetS. This would provide us with additional steps to understanding CVD mortality differences by race/ethnicity within the ORC population. In summary, obesity is the second most common prevention of cancer, and in study participants with MetS we found the adjusted prevalence of ORC to be higher in non-Hispanic Blacks and Hispanics than among non-Hispanic Whites. Therefore, strategies to increase awareness for cancer risk among non-Hispanic Blacks and Hispanics with MetS are warranted, as are prospective studies to determine whether MetS treatment can reduce ORC risk.

Acknowledgments

We would like to thank Gina Hamilton for project administration and Sharese Terrell Willis, PhD, for editing assistance.

Data Availability

Data availability statement: The data that support the findings of this study are openly available in NHANES at https://wwwn.cdc.gov/nchs/nhanes/, reference number 1999-2014.

Funding Statement

SM, BB, DK, NK-This research was supported by a grant from the National Heart, Lung, and Blood Institute to the University of Mississippi Medical Center (Grant #2R25HL126145 – MPIs Beech and Norris). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Steele CB, Thomas CC, Henley SJ, et al. Vital Signs: Trends in Incidence of Cancers Associated with Overweight and Obesity—United States, 2005–2014. MMWR Morb Mortal Wkly Rep. 2017;66(39):1052–1058. 10.15585/mmwr.mm6639e1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Hong Y-R, Huo J, Desai R, Cardel M, Deshmukh AA. Excess Costs and Economic Burden of Obesity-Related Cancers in the United States. Value Health. 2019;22(12):1378–1386. 10.1016/j.jval.2019.07.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Mehta P, Henry-Tillman R. Obesity-related cancer: an emerging need for more education. J Cancer Educ. 2008;23(4):201–203. 10.1080/08858190802470778 [DOI] [PubMed] [Google Scholar]
  • 4.Moore JX, Chaudhary N, Akinyemiju T. Metabolic Syndrome Prevalence by Race/Ethnicity and Sex in the United States, National Health and Nutrition Examination Survey, 1988–2012. Preventing chronic disease. 2017;14:E24–E24. 10.5888/pcd14.160287 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Sun J-W, Zhao L-G, Yang Y, Ma X, Wang Y-Y, Xiang Y-B. Obesity and risk of bladder cancer: a dose-response meta-analysis of 15 cohort studies. PloS one. 2015;10(3):e0119313–e0119313. 10.1371/journal.pone.0119313 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Bianchini F, Kaaks R, Vainio H. Overweight, obesity, and cancer risk. Lancet Oncol. 2002;3(9):565–574. 10.1016/s1470-2045(02)00849-5 [DOI] [PubMed] [Google Scholar]
  • 7.Wolk A, Gridley G, Svensson M, et al. A prospective study of obesity and cancer risk (Sweden). Cancer Causes Control. 2001;12(1):13–21. 10.1023/a:1008995217664 [DOI] [PubMed] [Google Scholar]
  • 8.Sturgeon KM, Deng L, Bluethmann SM, et al. A population-based study of cardiovascular disease mortality risk in US cancer patients. Eur Heart J. 2019;40(48):3889–3897. 10.1093/eurheartj/ehz766 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Kazanjian A, Smillie K, Howard AF, Ward A, Doll R. A structured approach to knowledge exchange: Understanding the implementation of a cancer survivor program. European Journal of Oncology Nursing. 2012;16(4):399–405. 10.1016/j.ejon.2011.09.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.de Haas EC, Oosting SF, Lefrandt JD, Wolffenbuttel BH, Sleijfer DT, Gietema JA. The metabolic syndrome in cancer survivors. Lancet Oncol. 2010;11(2):193–203. 10.1016/S1470-2045(09)70287-6 [DOI] [PubMed] [Google Scholar]
  • 11.Westerink NL, Nuver J, Lefrandt JD, Vrieling AH, Gietema JA, Walenkamp AM. Cancer treatment induced metabolic syndrome: Improving outcome with lifestyle. Crit Rev Oncol Hematol. 2016;108:128–136. 10.1016/j.critrevonc.2016.10.011 [DOI] [PubMed] [Google Scholar]
  • 12.Hodge AM, Bassett JK, Milne RL, English DR, Giles GG. Consumption of sugar-sweetened and artificially sweetened soft drinks and risk of obesity-related cancers. Public Health Nutrition. 2018;21(9):1618–1626. 10.1017/S1368980017002555 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Friedenreich CM, Cust AE. Physical activity and breast cancer risk: impact of timing, type and dose of activity and population subgroup effects. British Journal of Sports Medicine. 2008;42(8):636. 10.1136/bjsm.2006.029132 [DOI] [PubMed] [Google Scholar]
  • 14.Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey: sample design, 1999–2010. Available at: https://www.cdc.gov/nchs/data/series/sr_01/sr01_056.pdf.
  • 15.Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey: sample design, 2011–2014. Available at: https://www.cdc.gov/nchs/data/series/sr_02/sr02_162.pdf. Accessed February 6, 2017.
  • 16.Plan and operation of the Third National Health and Nutrition Examination Survey, 1988–94. Series 1: programs and collection procedures. Vital Health Stat 1. 1994(32):1–407. [PubMed] [Google Scholar]
  • 17.Hoyo C, Cook MB, Kamangar F, et al. Body mass index in relation to oesophageal and oesophagogastric junction adenocarcinomas: a pooled analysis from the International BEACON Consortium. International Journal of Epidemiology. 2012;41(6):1706–1718. 10.1093/ije/dys176 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Chen Y, Liu L, Wang X, et al. Body Mass Index and Risk of Gastric Cancer: A Meta-analysis of a Population with More Than Ten Million from 24 Prospective Studies. Cancer Epidemiology Biomarkers &amp; Prevention. 2013;22(8):1395. 10.1158/1055-9965.EPI-13-0042 [DOI] [PubMed] [Google Scholar]
  • 19.Chen Y, Wang X, Wang J, Yan Z, Luo J. Excess body weight and the risk of primary liver cancer: an updated meta-analysis of prospective studies. Eur J Cancer. 2012;48(14):2137–2145. 10.1016/j.ejca.2012.02.063 [DOI] [PubMed] [Google Scholar]
  • 20.Wang F, Xu Y. Body mass index and risk of renal cell cancer: a dose-response meta-analysis of published cohort studies. Int J Cancer. 2014;135(7):1673–1686. 10.1002/ijc.28813 [DOI] [PubMed] [Google Scholar]
  • 21.Jacobs EJ, Newton CC, Patel AV, et al. The Association Between Body Mass Index and Pancreatic Cancer: Variation by Age at Body Mass Index Assessment. Am J Epidemiol. 2020;189(2):108–115. 10.1093/aje/kwz230 [DOI] [PubMed] [Google Scholar]
  • 22.Kwon H, Han K-D, Park C-Y. Weight change is significantly associated with risk of thyroid cancer: A nationwide population-based cohort study. Scientific Reports. 2019;9(1):1546. 10.1038/s41598-018-38203-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Greenlee H, Shi Z, Sardo Molmenti CL, Rundle A, Tsai WY. Trends in Obesity Prevalence in Adults With a History of Cancer: Results From the US National Health Interview Survey, 1997 to 2014. J Clin Oncol. 2016;34(26):3133–3140. 10.1200/JCO.2016.66.4391 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Gee GC, Ford CL. STRUCTURAL RACISM AND HEALTH INEQUITIES: Old Issues, New Directions. Du Bois Rev. 2011;8(1):115–132. 10.1017/S1742058X11000130 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Faldoni FLC, Rainho CA, Rogatto SR. Epigenetics in Inflammatory Breast Cancer: Biological Features and Therapeutic Perspectives. Cells. 2020;9(5):1164. 10.3390/cells9051164 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Notterman DA, Mitchell C. Epigenetics and Understanding the Impact of Social Determinants of Health. Pediatr Clin North Am. 2015;62(5):1227–1240. 10.1016/j.pcl.2015.05.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Chebet JJ, Thomson CA, Kohler LN, et al. Association of diet quality and physical activity on obesity-related cancer risk and mortality in black women: Results from the Women’s Health Initiative. Cancer Epidemiology Biomarkers and Prevention. 2020;29(3):591–598. 10.1158/1055-9965.EPI-19-1063 [DOI] [PubMed] [Google Scholar]
  • 28.Chadid S, Kreger BE, Singer MR, Loring Bradlee M, Moore LL. Anthropometric measures of body fat and obesity-related cancer risk: sex-specific differences in Framingham Offspring Study adults. International Journal of Obesity. 2020;44(3):601–608. 10.1038/s41366-020-0519-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Frank T Spradley

8 Feb 2021

PONE-D-20-37144

Prevalence and Predictors of Obesity-Related Cancers Among Racial/Ethnic Groups with Metabolic Syndrome

PLOS ONE

Dear Dr. Monestime,

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PLOS ONE

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Comments to the Author

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Reviewer #1: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes

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5. Review Comments to the Author

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Reviewer #1: In manuscript entitled ‘Prevalence and Predictors of Obesity-Related Cancers Among Racial/Ethnic Groups with Metabolic Syndrome’ by Shanada Monestime et al., authors observe that obesity related cancers are more prevalent in Blacks and Hispanics, males and younger adults with metabolic syndrome.

I have several reservations for the study. My specific comments are appended as below:

1. Race and ethnicity is well known to be associated with the cancer aggressiveness. For instance, the death rate in African American females is 14% higher despite 7% low incidence rate (PMID: 30558195). There seems less novelty in the study reported.

2. While referring to the cardiovascular disease, authors cite relatively old reference while there are many recent evidences (PMID: 31761945, PMID: 28624099, PMID: 28421481). A careful review of cited literature is essential.

3. The authors claims that the data was obtained from 1999-2014 while the reference (reference no 13) they cite is published in 1994. This need to be explained.

4. Does authors specify past vs current individuals under medication for diabetes/hypertension?

5. While accessing the smoking status, does authors pay attention towards past/current smoker? It may not be relevant to classify a past smoker who at present does not smoke to classify in the third criteria (not at all a smoker).

6. Statistical inference should be quoted in the figures (Figure 1, 2).

7. As authors notes the observations in a range of cancer, it should be specified which cancer the obesity and metabolic syndrome related observations meet the statistical significance and what message authors like to spread through it?

8. Which cancers authors find the gender related disparity? How does authors reconcile it with hormone status?

9. As authors use only one source for the data, once the possible role of factors is identified, a careful review of literature could have conducted to justify the observations. For instance, the gender/ obesity related disparity among the observed cancers.

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Reviewer #1: Yes: Ravindra Deshpande

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PLoS One. 2021 Apr 7;16(4):e0249188. doi: 10.1371/journal.pone.0249188.r002

Author response to Decision Letter 0


11 Mar 2021

1. Reviewer’s comment: Race and ethnicity is well known to be associated with the cancer aggressiveness. For instance, the death rate in African American females is 14% higher despite 7% low incidence rate (PMID: 30558195). There seems less novelty in the study reported.

a. Response: Although it is known for African Americans to have high rates of several types of cancers, our study provides novelty because we performed a regression model to further understand if after considering sociodemographic factors, did racial differences exist with obesity related cancers? Interestingly, when we divided the cancers by obesity versus non-obese cancers, African Americans were linked to having higher rates of Obesity Related Cancers and Whites were linked to having higher rates of Non-Obesity Related Cancers.

2. Reviewer’s comment While referring to the cardiovascular disease, authors cite relatively old reference while there are many recent evidences (PMID: 31761945, PMID: 28624099, PMID: 28421481). A careful review of cited literature is essential.

a. Response The reviewer brought up a great point. Within my literature search, I have come across several recent articles between 2017-2020. The issue I am encountering is when I want to reference something from the newer articles, the statement within those articles refers back to another article (the original source) which are backdated to 2010-2014. However, I was able to update one of my references to reflect a more updated finding. Examples are below:

b. Response Although reference 9 dates back from 2010, this was a review article that discussed the pathophysiology of Mets as it relates to cancer. Several new studies refers back to this article so I used it to support my statements from primary literature.

3. Reviewer’s comment The authors claims that the data was obtained from 1999-2014 while the reference (reference no 13) they cite is published in 1994. This need to be explained.

a. Response Thank you for identifying this. I updated the references to reflect 1999-2014

4. Reviewer’s comment Does authors specify past vs current individuals under medication for diabetes/hypertension?

a. Response Within the study population section, we included key words to indicate that survey respondents had to currently be on treatment in order for us to identify if they had hypertension and/or diabetes. For example the questions regarding medications were:

i. Are you now taking prescribed medicine (for blood pressure)?”

ii. “Are you now taking diabetic pills to lower blood sugar?”

iii. Are you taking insulin now?”

b. Response We did not include patients with a past medication history because we wanted to identify current status of diabetes and/or hypertension. In this section we also assessed lab values to determine diabetes and/or hypertension.

5. Reviewer’s comment While accessing the smoking status, does authors pay attention towards past/current smoker? It may not be relevant to classify a past smoker who at present does not smoke to classify in the third criteria (not at all a smoker).

a. Response Thank you for your comment. We classified smoking status in three categories: smoking every day, some days, or not at all. Past smoking was categorized in the (not at all a smoker). Current smokers were broken down into the following two categories: smoking every day, some days. Do you mind providing clarity on the request and I am happy to update this portion of the manuscript?

6. Reviewer’s comment Statistical inference should be quoted in the figures (Figure 1, 2).

a. Response The statistical inference for Figures 1 and 2 are now located under the image. For figure 1, our statistical analysis focused on the frequencies.

7. Reviewer’s comment As authors notes the observations in a range of cancer, it should be specified which cancer the obesity and metabolic syndrome related observations meet the statistical significance and what message authors like to spread through it?

a. Response Thank you for this great comment. Our current funding supported a statistician to support one specific aim. Our aim was to assess if racial differences exist regarding the risks of having an obesity related cancer for patients with metabolic syndrome. Our study revealed that there is a significant risk difference by race. Therefore, we are submitting a second small grant to get funding for a statistician to assist us with determining if differences of ORC exist by gender and cancer type, while stratifying by race. Although we are unable to address cancer type into our current regression model, this manuscript serves as a foundation to demonstrate and support the next steps to identify differences by cancer types.

b. Response I removed comments regarding breast and colon cancer from the discussion due to this being an observation/speculation and not supported by our statistical analysis. This redirects our manuscript to focus on our main findings. Thank you again for the great feedback.

8. Reviewer’s comment Which cancers authors find the gender related disparity? How does authors reconcile it with hormone status?

a. Response Thank you for your excellent comment. Similar to the statement above, during our research, our primary aim focused on if racial differences exist in the risk of developing an ORC in the Mets population. Our study demonstrated that gender differences exist. Therefore, within our next small grant application we now have a foundation to support further assessing gender differences as it related to different cancer types

9. Reviewer’s comment As authors use only one source for the data, once the possible role of factors is identified, a careful review of literature could have conducted to justify the observations. For instance, the gender/ obesity related disparity among the observed cancers.

a. Response Thank you for your comment. We revised the discussion to focus on our primary aim which was to identify if racial differences exist in the risk level of developing an ORC while confounding for several factors which prior studies did not do. Research within the Mets and ORC space by race/ethnicity is limited, but we were able to identify two main studies Steele et al and Hong et al which are listed within our discussion. that supports our findings. Within these studies they did not conduct a regression model to consider confounders so it was difficult to truly know if race/ethnicity played a role. However, how study strengthen the current findings because we performed a regression model with pertinent confounders which confirms, even with confounders in the model, racial/ethnicity differences still exist.

b. Response In regards to gender differences, we were unable to find anything in Steele or Hong et al. however, we mentioned how we could use information from Chadid et al. to further analyze this data by BMI, which we plan on conducting for our second study. We needed justification as to why studying gender differences by cancer type is critical and believe our findings will serve as a foundation.

Attachment

Submitted filename: Response Letter for PLOS ONE.docx

Decision Letter 1

Frank T Spradley

15 Mar 2021

Prevalence and Predictors of Obesity-Related Cancers Among Racial/Ethnic Groups with Metabolic Syndrome

PONE-D-20-37144R1

Dear Dr. Monestime,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Frank T. Spradley

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors have now answered all my comments and manuscript in present form is much better. I approve it for publication.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Ravindra Pramod Deshpande

Acceptance letter

Frank T Spradley

22 Mar 2021

PONE-D-20-37144R1

Prevalence and Predictors of Obesity-Related Cancers Among Racial/Ethnic Groups with Metabolic Syndrome

Dear Dr. Monestime:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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PLOS ONE Editorial Office Staff

on behalf of

Dr. Frank T. Spradley

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response Letter for PLOS ONE.docx

    Data Availability Statement

    Data availability statement: The data that support the findings of this study are openly available in NHANES at https://wwwn.cdc.gov/nchs/nhanes/, reference number 1999-2014.


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