The launch blog last month summarized a strand of literature that establishes the higher likelihood of death among women vis-à-vis men in developing-country settings – at every life stage, not just at birth or early childhood. Following Amartya Sen’s thesis on “missing women” (1990, 1992), the bulk of empirical evidence on this phenomenon across India, China and Africa, has been provided by Anderson and Ray (2010, 2012, 2017, 2019). The researchers acknowledge that their accounting exercise – focused on breaking down aggregate missing women numbers by age, disease, and geography – cannot disentangle the various explanatory factors. While genes or lifestyle may also be playing a role in these gendered outcomes, they put forth the possibility that women seek or receive medical care less often than men in low- and middle-income countries.
Pursuing this line of thought further, Ray collaborated with Jayaraman and Wang (2014) to study the diagnostic outcomes of 60,000 patients at an eye hospital in South India. They find that, at the time of presentation, women have worse diagnoses than men with regard to symptomatic illnesses. This indicates that males (or their parents) are more responsive to their perceptions of ill-health, leading to early care-seeking as compared to women. In terms of asymptomatic disease, there is no discernable gender gap, implying that either both females and males go for preventive health checkups at similar intervals, or – more plausibly – they do not go in for such checkups at all.
Several other studies at larger scales have sought to examine whether women access healthcare less than men do. However, a challenge in attributing gender gaps in healthcare utilization at the facility level to different healthcare-seeking by women and men, is that these may partly be caused by underlying differences in healthcare needs of women and men. In other words, females visit hospitals less than men simply because they require relatively less healthcare. A curation of the relevant literature, which is discussed in this blog, exhibits a range of methodological approaches to rule out this alternative reasoning.
“Missing” female hospital visits
In a 2019 study, Kapoor et al. analyze data from all outpatient visits in a calendar year at a prominent, publicly funded, tertiary hospital in the Indian capital city of New Delhi, with a large referral base in the region. The study attempts to estimate “missing” female patients, that is, the difference in the actual number of female patients and the number of female patients that should have visited the hospital had male and female patients come in the same proportion as the sex ratio of the overall population. Excluding obstetrics and gynecology, the sex ratio of hospital visits (sample of 2.38 million visits, by 882,324 unique patients) is shown to be 1.69 males to one female outpatient visit, which is higher than the population sex ratio in the region (1.09) as per the latest available Census data. Notably, the gender gap is worse in the younger (sex ratio of 1.94 for children and 2.02 for young adults) and older age groups (1.72 for those over 60 years of age), and for those who live in states that are farther away from Delhi. The authors contend that the findings likely reflect gender bias rather than gender-differentiated disease infliction, as the analysis involves multiple medical specialties and adjusts for hospital department-specific effects.
In a similar vein, Dupas and Jain (2024) examine the beneficiaries of a publicly subsidized health insurance program in the northwestern state of Rajasthan in India. While the program entitled beneficiaries to free inpatient care at a network of public and private hospitals, patients still bear out-of-pocket expenses in the form of diagnostics, medicines, travel to the hospital, and so on. The researchers apply a gender lens to 4.2 million hospital visits under the program over a period of four years, while taking into account local sex-specific illness prevalence estimates and the population sex ratio. It is observed that only 45% of the total visits are by females. In the under-10 age group, females constitute 33% of the total hospital visits, while the figure is 43% for those older than 50 years. The underrepresentation of women is particularly significant in private and high-cost tertiary care. Distance from hospital exacerbates gender gaps in this case too.
The authors conclude that without policy actions that specifically target women, public funding for healthcare will effectively remain pro-male. This is a weighty insight for India’s healthcare policy: in recent years, the key instrument for expanding secondary and tertiary healthcare access has been publicly funded health insurance for the poor. Under these programmes, benefits are provided on a ‘family-floater’ basis, with no special provisions for women.
In Southern China, Song and Bian (2014) collected data on 156,887 male and female patients from the medical record management system of a general hospital affiliated with the China Ministry of Health. The dataset spans a period of seven years, and includes patients admitted for surgical as well as medical treatments. It is found that fewer females were admitted to the hospital than males, with the exception of the 15-35 years age group, encompassing the prime childbearing ages of the 20s and 30s. Among those aged under 15 years or over 65 years, the male-to-female ratio is 1.6 (versus 1.1 for the study sample as a whole). Men had longer hospital stays than women and incurred greater expenses, even under the same disease conditions. In the researchers’ view, Chinese women have less power within the household and lower access to resources, and hence, prioritize the health of male family members above their own. They advocate for greater attention towards gender and equity in health in China.
Beyond hospital data: Insights on healthcare-seeking from surveys
While the above studies are largely based on hospital data, research in Nigeria by Cavatorta, Janssens and Mesnard (2021) brings together information on the entire portfolio of local healthcare providers in rural Kwara State with household survey data on the incidence of injuries or acute illnesses. The objective of the study is to develop insights into gender disparities in healthcare utilization in this low-resource setting in the North-Central part of the country. In line with other such work, they exclude women-specific healthcare pertaining to sexual and reproductive health. They also restrict the sample to those reporting as suffering from injuries or acute illnesses, such that the male-female healthcare-seeking comparison is not muddled by any systematic variation in the requirement for healthcare across genders. It is demonstrated that women have a greater propensity than men to forgo formal healthcare when the price increases. Their price sensitivity is likely driven by their lower bargaining power in household decision-making. Although distance plays a role in healthcare-seeking, women are not more sensitive to this factor than men.
In China, Jun, Raven and Tang (2007) examine the use of inpatient care among the elderly in urban regions, based on data from the national household health interview surveys conducted in 1993, 1998, and 2003. They show that non-hospitalization – defined as not utilizing inpatient services despite being referred by doctors for hospital admission – was greater among elderly women than their male counterparts, at 31.9% and 20.2% respectively, in the year 2003. Looking at trends over the 10-year period of the survey data, although non-hospitalization rates declined for both genders, the reduction was statistically insignificant in the case of females. Low income and the lack of health insurance emerge as key constraints on the access of inpatient care, and women are found to be more vulnerable on both fronts.
Batra, Gupta and Mukhopadhyay (2018) analyse gender differences in treatment-seeking for cancer (types that are common to women and men, for example, lung cancer), based on a primary longitudinal survey of 208 rural patients at a public tertiary health center in the state of Odisha in eastern India. It is found that the average cumulative expenditure over the period between the first symptom and one year after registering at the tertiary center, is lower for female patients than males and the gap widens with age. This is despite there being no significant gender differences in the probability of being an advanced cancer patient. Rather, the disparity primarily emanates from women being less likely to get treatment for their disease before coming to the tertiary center. For ailing rural residents, the tertiary center is often not the first point of contact. Especially in the case of diseases such as cancer, the economic burden begins with the occurrence of symptoms, on account of diagnostic tests and symptomatic care.
Gender-differentiated medical treatment
So far, it is seen consistently that women are seeking formal healthcare less than their male counterparts, and these disparities cannot be explained by differences in healthcare needs across genders. But for the women that do reach health facilities, is the medical treatment the same as men, for any given illness?
In the eye hospital study, Ray, Jayaraman and Wang (2014) find no gender differences in indicators such as time to surgery, duration of surgery, incidence of postoperative complications, and the seniority of attending medical personnel. However, most studies in this literature in the developing countries focus on access and not medical treatment. In developed countries, on the other hand, unequal treatment based on gender as well as race, has received a great deal of attention in research.
This work is rooted in two pivotal studies published in The New England Journal of Medicine in 1991, which demonstrated the prevalence of sex bias in the management of coronary heart disease. Essentially, female patients admitted to the hospital were less likely than male patients to undergo diagnostic procedures or interventions, even after controlling for socioeconomic characteristics and clinical conditions (Ayanian and Epstein 1991, Steingart et al. 1991). This evidence is reflective of decades of male-centered research that shaped diagnostic standards and perpetuated the myth that coronary artery disease is primarily a male condition. In her editorial for the same issue of NEJM, Dr Bernadine Healy coined the term ‘Yentl Syndrome’, to convey that women receive equitable medical treatment only when their symptoms mirror those typically seen in men. This understanding paved the way for other studies such as Chang et al. (2007) who show that female patients with potential acute coronary syndrome receive fewer cardiac catheterizations as compared to male patients, even when accounting for presenting complaints (for example, pressure or tightness in the chest), history or diagnostics.
Research has also underscored how gender discrimination in medical treatment may be compounded by race. Enzinger et al. (2023) examine trends in opioid access for pain management among older patients dying of cancer. They demonstrate that White women, on average, receive less morphine milligram equivalents per day (MMED) than White men, but the dosage is even lower among Black women. Black patients are also more likely to be subjected to Urine Drug Screen.
However, in 2010, Chandra and Staiger argue that when there are apparent treatment disparities based on social identity, one must distinguish between prejudice and statistical discrimination. While prejudice implies that physicians consciously or unconsciously withhold treatment from minority groups despite similar benefits, statistical discrimination is based on the physician’s knowledge that gender or race are associated with lower benefits from treatment. Their analysis of data on heart attack treatments does not provide empirical support for the prejudice hypothesis.
There is a need to explore the aspect of differential medical treatment at facilities based on gender and other facets of socioeconomic identity (such as caste in India), which may intersect with gender to potentially create marginalisation in healthcare.
A lot of the studies discussed in this blog reveal that gender gaps in seeking healthcare are larger for younger and older age groups. There is more parity in the middle age groups, even when excluding gynecology and obstetrics – hospital departments where care-seeking by women is directly related to childbearing. In the next blog at the end of August, we will turn the spotlight on how the intersection of health and gender in less-developed settings has largely been about maternal and child health. However, with the disease burden shifting towards non-communicable diseases, there is a need to take a wider view of women’s health. In the context of non-communicable diseases, women’s lower healthcare-seeking is concerning since delayed diagnosis implies worse treatment outcomes.
FOOTNOTES
1 Dr Healy bases the term on Yentl, the 19th century heroine of Issac Bashevis Singer’s short story, who had to disguise herself as a man to attend school and study the Talmud – the central text of Rabbinic Judaism.
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