| Literature DB >> 35604515 |
Ewelina Biskup1,2, Alberto M Marra3,4, Immacolata Ambrosino5, Elena Barbagelata6, Stefania Basili7, Jacqueline de Graaf8, Asunción Gonzalvez-Gasch9, Risto Kaaja10, Eleni Karlafti11, Dor Lotan12, Alexandra Kautzky-Willer13,14, Maria Perticone15, Cecilia Politi16, Karin Schenck-Gustafsson17, Andreia Vilas-Boas18, Jeanine Roeters van Lennep19, Emma A Gans20, Vera Regitz-Zagrosek21,22, Louise Pilote23, Marco Proietti24,25,26, Valeria Raparelli27,28,29.
Abstract
Sociocultural gender is a complex construct encompassing different aspects of individuals' life, whereas sex refers to biological factors. These terms are often misused, although they impact differently on individuals' health. Recognizing the role of sex and gender on health status is fundamental in the pursuit of a personalized medicine. Aim of the current study was to investigate the awareness in approaching clinical and research questions on the impact of sex and gender on health among European internists. Clinicians affiliated with the European Federation of Internal Medicine from 33 countries participated to the study on a voluntary basis between January 1st, 2018 and July 31st, 2019. Internists' awareness and knowledge on sex and gender issues in clinical medicine were measured by an online anonymized 7-item survey. A total of 1323 European internists responded to the survey of which 57% were women, mostly young or middle-aged (78%), and practicing in public general medicine services (74.5%). The majority (79%) recognized that sex and gender are not interchangeable terms, though a wide discrepancy exists on what clinicians think sex and gender concepts incorporate. Biological sex and sociocultural gender were recognized as determinants of health mainly in cardiovascular and autoimmune/rheumatic diseases. Up to 80% of respondents acknowledged the low participation of female individuals in trials and more than 60% the lack of sex-specific clinical guidelines. Internists also express the willingness of getting more knowledge on the impact of sex and gender in cerebrovascular/cognitive and inflammatory bowel diseases. Biological sex and sociocultural gender are factors influencing health and disease. Although awareness and knowledge remain suboptimal across European internists, most acknowledge the underrepresentation of female subjects in trials, the lack of sex-specific guidelines and the need of being more informed on sex and gender-based differences in diseases.Entities:
Keywords: Biological sex; Education; Internal medicine; Personalized medicine; Sociocultural gender
Mesh:
Year: 2022 PMID: 35604515 PMCID: PMC9352607 DOI: 10.1007/s11739-022-02951-9
Source DB: PubMed Journal: Intern Emerg Med ISSN: 1828-0447 Impact factor: 5.472
Examples of how sex and gender influence on health and diseases[5, 11]
| Area | Example physiology/pathology | Sex-based considerations | Gender-based considerations |
|---|---|---|---|
| Genetics | X chromosome. Y chromosome. Parental Imprinting. | Sex differences in gene regulation due to X chromosome inactivation and autosomal-like regions contained in the X chromosome | – |
| Epigenetics | DNA methylation. Histone modification. Gene silencing by noncoding RNA | Sex dimorphism and genetic variation driven by endogenous sex-specific hormones | Diet, exercise, cigarette smoking, environmental toxins, and psychosocial stress modify gene expression. |
| Pharmacology | Pharmacodynamics Pharmacokinetics | Sex differences in absorption, distribution, metabolism, and elimination of pharmacological agents. Higher incidence of adverse drug reactions in females. | Gender-related factors (e.g., greater caregiving responsibilities, trauma exposures) influence the efficacy of behavioral treatments of addiction in women and transgender individuals. Medication adherence can be influenced by gender-related factors. |
| Cardiovascular system | Cardiovascular diseases | Prevalence, clinical manifestations and outcomes, and response to main cardiovascular therapies differ by sex (e.g., obstructive vs non-obstructive coronary artery disease; higher mortality in young females with acute myocardial infarction). Sex-specific risk factors (e.g., eclampsia, gestational diabetes). A disproportionate percentage of stroke deaths in females. | Exposure to detrimental social determinants of health (such as poverty, low education, and health literacy, insurance coverage) influences cardiovascular outcomes. Treatment disparities due to insufficient recognition of different symptomatology |
| Liver function | Liver function | Sex-differences in disease susceptibility (higher risk of primary sclerosing cholangitis, chronic viral hepatitis, cirrhosis, and hepatocellular carcinoma in males; higher risk of primary biliary cholangitis and autoimmune hepatitis in females). Sex-based response to therapies (non-alcoholic steatohepatitis resolution with moderate body weight loss for males whereas much greater weight reduction in females is needed). | Women follow healthier diets by eating more vegetables and fruits and less meat and fat than men so that they are less at risk of non-alcoholic fatty liver disease |
| Kidney function | Chronic kidney diseases | Higher prevalence in females; sex-specific risk (hypertensive disorders of pregnancy). More rapid rate of progression in the impairment of renal function in males. | Gender biases in renal transplant allocation |
| Respiratory system | Chronic obstructive pulmonary diseases (COPD) asthma | In females, early onset of COPD with less tobacco exposure and higher exacerbation rates than males. Higher prevalence of asthma in middle-aged females. More likely premenstrual asthma that improves after menopause | Gender-based change in smoking habits Gendered stereotypes driving misdiagnosis in women |
| Immune function | Autoimmune disorders | Sex dimorphism in prevalence of autoimmune diseases (innate and adaptive immune responses are stronger (e.g., higher vaccine efficacy) in females than males. | Gender-specific environmental exposures can induce vitamin D levels differences |
| Neurocognitive aging process | Alzheimer disease | Prevalence and rapid progression of cognitive impairment in females. Sex-specific effect in carriers of the APOE*E4 allele. | Gender-specific behavioral and lifestyle factors (e.g., smoking, regular physical activity) significantly influence brain aging. Greater burden of disease caregiving in women. |
| Mental health | Depression | Symptomatology partially different. Women have a higher predisposition to depression. | Men do seek treatment less than women but when they do, they are less likely to be diagnosed with major depressive disorder regardless of their scores on standardized measures of depression like those of women. |
| Intersection with healthcare system | Accessibility/barriers to care | Sex differences in the burden of several diseases requiring hospitalization or access to outpatient services. | Discrimination related to gender identity. Financial and non-financial (e.g., caregiving, transportation) barriers to accessing health care and treatment. |
Baseline characteristics of survey’s participants
| Survey cohort | OR (95% CI) | ||
|---|---|---|---|
| Sex, | |||
| Male | 564 (42.6) | 1.48 (0.17–12.81) | 0.72 |
| Female | 753 (56.9) | 1.27 (0.15–10.90) | 0.83 |
| Other | 6 (0.5) | Ref. | Ref. |
| Age, years mean (SD) | 42.3 (12.6) | 0.99 (0.98–1.01) | 0.40 |
| Age classes, | |||
| 180 (13.6) | 0.91 (0.33–2.48) | 0.86 | |
| 30–39 | 498 (37.6) | 1.29 (0.51–3.29) | 0.59 |
| 40–49 | 252 (19.0) | 1.64 (0.65–4.14) | 0.29 |
| 50–59 | 232 (17.5) | 1.31 (0.53–3.23) | 0.56 |
| 60–69 | 126 (9.5) | 1.25 (0.48–3.23) | 0.64 |
| ≥70 | 35 (2.6) | Ref. | Ref. |
| European region, | |||
| Northern Europe | 34 (2.6) | 0.88 (0.24–3.24) | 0.85 |
| Western Europe | 578 (43.7) | 2.29 (0.51–10.28) | 0.28 |
| Eastern Europe | 27 (2.0) | 0.84 (0.23–3.09) | 0.79 |
| Southern Europe | 670 (50.7) | 1.82 (0.42–7.90) | 0.42 |
| Non-EU countries | 13 (1.0) | Ref. | Ref. |
| Work setting, | |||
| General/primary care | 1,126 (85.1) | Ref. | Ref. |
| Specialized care | 77 (5.8) | 0.89 (0.50–1.59) | 0.69 |
| Research centre | 29 (2.2) | – | – |
| Other | 91 (6.9) | 1.47 (0.91–2.37) | 0.11 |
| Type of practice, | |||
| Public | 989 (74.8) | 1.28 (0.70–2.35) | 0.42 |
| Private | 37 (2.8) | 0.81 (0.29–2.22) | 0.68 |
| Public and private | 204 (15.4) | 1.12 (0.66–1.92) | 0.67 |
| Other | 93 (7.0) | Ref. | Ref. |
| Role, | |||
| Junior physician | 424 (32.0) | 0.90 (0.47–1.75) | 0.76 |
| Attending physician/GP | 595 (45.0) | 1.17 (0.65–2.13) | 0.60 |
| Senior physician | 226 (17.1) | 1.25 (0.68–2.29) | 0.48 |
| Other | 78 (5.9) | Ref. | |
| Specialty, | |||
| Internal medicine/geriatric | 803 (60.7) | 0.86 (0.61–1.21) | 0.37 |
| Intensive care | 33 (2.5) | 1.04 (0.72–1.50) | 0.82 |
| Clinical sub-specialties | 210 (15.9) | 1.16 (0.51–2.61) | 0.73 |
| Physician in training/other | 277 (20.9) | Ref. | |
| Practice years, mean (SD)* | 15.3 (12.5) | 0.99 (0.98–1.00) | 0.22 |
| Practice years, | |||
| 0–4 | 292 (22.1) | Ref. | Ref. |
| 5–9 | 293 (22.1) | 0.79 (0.53–1.18) | 0.26 |
| 10–19 | 290 (21.9) | 1.05 (0.71–1.54) | 0.81 |
| 20–39 | 365 (27.6) | 0.87 (0.60–1.26) | 0.46 |
| ≥40 | 76 (5.7) | 0.57 (0.28–1.14) | 0.11 |
GP General Practitioner, SD Standard Deviation
*Data available in 1316 participants
Fig. 1Degree of agreement and disagreement on sex and gender-based statements in the overall cohort (Panel 1A) and stratified by sex (Panel 1B)
Identification of sex and gender-related factors among the overall cohort of surveyed participants
| Sex related (%) | Gender related | Sex and gender related (%) | No sex and gender related (%) | Don’t know (%) | |
|---|---|---|---|---|---|
| Body size | 49.9 | 15.0 | 14.6 | 17.9 | 2.6 |
| Genetics | 66.4 | 11.5 | 12.8 | 6.0 | 3.4 |
| Sex hormones | 66.1 | 11.7 | 18.7 | 1.5 | 1.9 |
| Reproductive status | 64.0 | 12.9 | 16.9 | 3.5 | 2.7 |
| Body composition | 54.0 | 18.8 | 20.2 | 4.8 | 2.2 |
| Diet | 8.3 | 32.9 | 14.2 | 40.1 | 4.5 |
| Marital status | 10.6 | 41.6 | 12.9 | 27.6 | 7.3 |
| Personality traits | 6.8 | 44.7 | 21.1 | 20.6 | 6.8 |
| Socio-economic status | 6.9 | 35.4 | 17.6 | 35.4 | 4.7 |
| Working status | 8.9 | 38.8 | 17.2 | 31.6 | 3.6 |
| Alcohol | 9.9 | 34.8 | 12.2 | 39.6 | 3.4 |
| Smoking habit | 8.0 | 34.0 | 11.3 | 42.2 | 4.5 |
| Ethnicity | 8.2 | 20.6 | 5.1 | 59.9 | 6.2 |
| Religion | 2.2 | 22.3 | 4.2 | 64.9 | 6.4 |
| Age | 22.4 | 10.4 | 8.2 | 54.9 | 4.2 |
| Comorbidities | 33.1 | 18.9 | 21.8 | 22.1 | 4.1 |
| Disability | 7.1 | 13.5 | 6.3 | 63.7 | 9.3 |
| Geographic Location | 4.1 | 16.0 | 3.9 | 66.6 | 9.4 |
| Environment | 4.3 | 30.7 | 8.8 | 45.7 | 10.5 |