Articles

The Case for Gender Equityin Health Research

Gita Sen, Asha George and Piroska Östlin

Attention to health equity on the basis of economic class, caste or race has not spilledover to an effective consideration ofgender. Yet, social bias not only heavily influenceshealth outcomes between women and men, it also affects our very understanding ofbiological differences with implications for understanding gender equity. Hence,when considering biological differences or special gender needs, it is necessary to beaware that biological ’givens’ can also mask social norms that sanction discriminationand perpetuate health inequities. It is, therefore, particularly crucial to understandthe nuances found in a gender and health equity approach and the consequences ofnot taking gender seriously in health research. These include the neglect of certainareas through resounding silences, the existence of misdirected or partial approaches,and the poor recognition of interactive pathways in terms of co-morbidity and multi-ple social processes. After detailing this background we review the literature on thegender paradox’ in health from an equity perspective. Finally, we discuss how researchcan contribute to improving gender equity and health by being conscious of potentialbiases in data, methodology and clinical research.

Introduction

Health sciences have been concerned with health inequity at least sincethe early part of the 19th century, when the distinctions between thehealth status of rich and poor were recognised to be pervasive (Farr1839; Rosen 1958).1 Such distinctions are also seen to be causally inter-active with other determinants of inequality, such as race and caste(Williams 1997). Yet, this attention to health equity on the basis of

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economic class, caste or race has not spilled over to an effective consid-eration of gender.’

In part this is because of the still common fallacy of conflating genderwith biological difference. Although the distinction between sex (asbiologically determined) and gender (as socially constructed) has beenextensively used in the social sciences, doing this in the health fieldposes two challenges:

1. In health, biology cannot simply be wished away as bias. Wecannot avoid considering how biology and social factors interactwhen exploring health-related differences between women andmen.

2. Health differences between men and women may be more in-fluenced by biology than health differences between rich and poor,or between caste or racial groups.

Nevertheless, social factors and processes can be just as importantfor health differentials between women and men. For example, apartfrom being biologically more vulnerable due to pregnancy (Diwan etal. 1998), poor women are also more vulnerable to morbidity frommalaria (than both rich women and poor men) due to poorer access toquality health care services and adequate nutrition. Rarely does biologyact alone to determine health inequities. In many circumstances socialdisadvantages may even be the prime determinants of unfair healthoutcomes. For example, women’s lower social autonomy and structuraldisadvantage exacerbate their biological susceptibility to HIV (Weissand Rao Gupta 1998; Zierler and Krieger 1997). Excess fatalities andinjury due to traffic accidents among men may be due to the genderedphenomenon of who drives and owns cars, and a promotion of risk-taking through the marketing of maleness (Snow 2002).

Social bias also affects our very understanding of biological processes.Western medicine has often legitimised the association of disease andweakness with women.’ For instance, menstruation and menopauseare still described as being processes of wasted production and signs ofbiological decay (Martin 1990). These negative perceptions, apart frombeing harmful in themselves, also serve to sanction explicit and implicitdiscrimination against women’s active participation in society due totheir supposed biological frailty (Lupton 1994).4 For example, anthro-pologists note how the salience of premenstrual syndrome (PMS) grew

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parallel to women’s claims for full participation in public domains(Rittenhouse 1991).

Hence, when considering biological differences or special needs forgender and health equity, it is necessary to be aware that biological’givens’ can also mask social norms that sanction discrimination andperpetuate health inequities. If it is true, as we argue in this paper, thatmany health outcomes are not the result of ’natural’ biological processesbut are due to societal influences, then they can and ought to be changedthrough health and social policy.

Gender Bias, Equality and Equity

Gender bias refers to unequal access for women and men to materialand non-material resources, reproduced through symbolic culturalnorms and values. This defines male and female behaviours, expect-ations and roles, as well as relations between and among women andmen (Rathgeber and Vlassoff 1993). Gender influences not only rela-tions between individuals, but also the institutions constituting humansocieties.

Yet, research often defines gender solely as a set of social roles. Incontrast, research on race or class dynamics does not refer to class orrace roles.

The reliance on roles as an analytical concept surfaces primarily inrelation to gender (rather than race or class) and testifies to a tendencywithin policy circles to treat gender in isolation from the structuralperspectives that infoi-m the analysis of these other forms of socialinequality. (Kabeer 1994)

This leads to a focus on behaviour change at the individual level, with-out analysing the structural inequalities that may underpin such rolesand behaviour, and the required policy changes at the societal level(Stronks et al. 1996). As a result, socially subordinate groups are oftenvictimised or blamed for their own disadvantaged situations. Rapevictims are all too often accused of provocative dress or behaviour,and teenage mothers are blamed for irresponsibility. Working womenare presumed to be neglectful mothers and thus responsible for the illhealth of their children.

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This problem is not unique to gender. Factors such as economicclass, race, caste, ethnicity or sexual orientation have not fared muchbetter in this regard. By not exploring the range of potential underlyingfactors that may contribute to social inequalities in health, the per-ception is reinforced that current ill health status is inherent in theindividual or social group under observation (Lillie-Blanton and LaVeist1996). At best this results in ’conceptual paths that have little or norelevance to the way people actually live, and hence inevitably tostrategies and policies that have no relevance to prevention’ (Clatts1995). At worst, by obscuring the relations of power that provide thefoundation for discrimination, we depoliticise and perpetuate these’monotonous’ realities (Farmer 1997).

Defining gender as relations of power requires us to focus system-atically on the forms that bias takes and the resultant inequality andinjustice. In doing this in fields other than health, feminist analystshave preferred to use the concept of gender equality as the foundationof notions of gender justice or equity.5 Such a position is less tenablein health because of the confounding influence of biology. Even whenbiology itself is scrutinised through a gender lens, as we have argued

, earlier, this clearly does not eliminate all biology-related differencesbetween women and men. Absence of difference or gender equality assuch cannot therefore be the uniform foundation for gender justice inhealth. Indeed, equality of health outcomes may even in some instancesbe a marker for gender injustice, because it may indicate that women’sparticular biology-dependent needs or abilities are not adequatelyrecognised.6 6

Gender equity in health must, therefore, stand on its own foundation:the absence of bias. But not being able to draw on a simple universalprinciple such as equality does complicate our task, because it neces-sitates an even more careful interrogation of where bias is present andhow it works. Our approach is based on the following principles:

1. Where genuine biological difference clearly interacts with socialdeterminants to define differential needs and experiences forwomen and men in health, gender equity may require qualitativelydifferent treatment that is sensitive to these specific needs.

2. Where there is no plausible biological reason for differentialoutcomes, social discrimination should be considered a primesuspect for causing unreasonable health outcomes. Here the

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recognition that differences are maintained by social discrim-ination requires that health equity measures focus on policiesthat encourage equal outcomes. This may require differentialtreatment to overcome historical discrimination.

These two principles provide the basis for deliberating the fairness ofan approach or intervention on the basis of its ability to promotehealth and protect rights to social well-being. A gender and healthequity analysis insists that, although differences in health needs betweenwomen and men do exist in relation to biological and historicaldifferences, this does not ’naturally’ lead to or justify different or un-equal social status or rights in just societies.

Consequences of Not Taking Gender Seriously:Resounding Silences

One way in which gender bias manifests in health is through the slowrecognition of health problems that particularly affect women. Onenot-so-distant and now well-known example is the case of reproductivetract infections (RTIs), particularly among poor women in developingcountries. Despite more than 50 years of globally and nationally sup-ported family planning programmes and extensive related research intocontraceptive behaviour, it is only within the last 10 years that seriousresearch into the prevalence of RTIs has occurred (Bang et al. 1989;Germain et al. 1992). Another example is that of domestic violence(Garcia Moreno 2002).While both these problems are now being addressed, they do not

exhaust the possible list of such silences. It is useful to remember that,when speaking about poorly acknowledged health problems, it is onlypossible by definition to speak about what we have already learned.What is striking in relation to the problems mentioned here is howwidespread their incidence is, how significant their effects are, andhow long it has taken health professionals to recognise them.

Misdirected or Partial Approaches

Misdirected or partial approaches exist across a broad range of healthsub-fields. In the field of environmental health, it has been generallypresumed that, as far as air pollution is concerned, rural areas. are cleaner

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than urban areas and that since the problem is one caused by industryand road traffic in urban areas, it does not discriminate between womenand men. This is a classic example of a partial approach that has misseda major source of environmental risk for women because it did notstart from awareness as to where women and men spend large parts oftheir working day. Recent evidence suggests that indoor air pollutionfrom cooking fires may not only be associated with greater cardiovas-cular morbidity in poor women, but may also be associated with higherrisks of TB, hisgher levels of blindness and inhibited nutrient uptake(Ostlin 2002; Sims and Butter 2002).

Occupational health has been similarly short-sighted in recognisingthe consequences of the differences in women’s and men’s work loca-tions and responsibilities. For example, a study in Sweden found thatovertime for men leads to a lower incidence of heart attack, but over-time for women leads to an increased risk of heart attack (Alfredssonet al. 1985, cited in bstlin 2002). Research also found that stress levelsof male managers tend to decline towards the end of the paid workday,while those of female managers tend to increase sharply in anticipationof domestic work requirements (Ostlin 2002). Although domestic workis presumed to be more leisurely, slower paced and under the controlof women, growing evidence suggests that the reality is rather different.The health implications involve an as yet poorly researched combin-ation of stress and depression (ibid.).

Such evidence points to how determinants of health inequity betweensocial groups may differ from determinants of average health across

populations (Whitehead et al. 2001). For example, working conditionsin Sweden are relatively good; hence, they do not have much explana-tory power over aggregate morbidity. But they do explain quite a lot ofthe health differential between socio-economic groups, especially whengender bias and the sexual division of labour are also taken into account.

Yet, women’s occupations generally have received less attention interms of measurement of health implications than men’s occupationsdespite considerable evidence that, by and large, women and men simplydo not do the same kind of work (Anker 1998). We know very littleabout the health impact of women’s work in agriculture or in smalland medium-sized factories and enterprises. Of special concern is theinformal sector where the overwhelming majority of women areemployed in many regions of the world.

Other fields have suffered from biased approaches rather than neglect.As is well known, early beliefs in the field of mental health traced

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women’s problems to their reproductive biology, as the very word’hysteria’ attests. Such axiomatic presumptions are not as far behindus as we might suppose or wish. Research today continues to focus onthe hypothesised relationship between reproduction-related events likemenstruation, pregnancy and menopause and women’s higher rates ofdepression. However, none of these events by themselves explain genderdifferences in depression (Astbury 2002). Not only has such bias neg-lected the role of reproduction on men’s mental health, but it has alsoled to delays in discovering non-reproductive aspects of depression inwomen, like the higher risk for cardiovascular morbidity (Musselmanet al. 1988, cited in Astbury 2002).

Ironically, while women’s reproductive biology was being linkedin questionable ways to their mental health, the real implications ofgender power relations around sexuality and reproduction for violenceand depression were ignored (Cottingham and Myntti 2002). Ongoingresearch on domestic violence suggests strong links between physicaland emotional/psychological abuse on the one hand and depressionon the other through a powerful mix of humiliation and entrapment(Astbury 2002; Garcia-Moreno 2002).

Similarly, the current public health response to hip fracture, empha-sising promotion of bone mineral density screening and therapeuticdrugs, is unlikely to have substantial impact. Instead, determinantsthat warrant further research include isolation among the elderly, phys-ical attributes and exercise, infrastructural changes that reduce the riskof falling, and possibly some features of traditional diets (Snow 2002).

Poor Recognition of Interactive Pathways

Co-morbidity, the simultaneous presentation of different diseases with-in a patient, is not inherently a sex-differentiated phenomenon. How-ever, particular aspects are of concern from a gender perspective. Forexample, malaria leads to higher risks of severe anaemia in women.This combined risk is particularly dangerous during pregnancy andcontributes significantly to maternal mortality in low-income countries.Schistosomiasis is associated with greater risks of infertility, abortionand vulnerability to HIV infection (Feldmeier et al. 1993, cited inHartigan et al. 2002). Although both these are well known at the levelof research and general policy recommendations, little has been doneto actually devise or test strategies for addressing them in the field.Focusing on reducing malaria risk for reproductive women in particular

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or reducing anaemia among girls and women generally are approachesthat do not require new clinical trials, but are predicated on a morewomen-friendly approach to health programmes.

The other source of interactions is the interplay among social factors.Gender is a distinct yet interactive social determinant, as other socialfactors can deepen or counteract the effect of gender on health out-comes. The resulting health differences may not be uniform or evenmove in the same direction. For example, the expected differences be-tween the polar extremes of the social gradient, that is, between rich,white men on the one hand and poor, coloured, women on the otherare largely confirmed through health research in the United States(Breen 2002). Nonetheless, there is no obvious or linear pattern as onemoves along the social gradient. In the absence of general unemploy-ment benefits, welfare policies that targeted poor women with depend-ent children led to worse health care access for poor men in the UnitedStates (ibid.). In India class-based inequalities in access to health serviceshave clearly worsened for both men and women during the last decade.However, the change in class gradients for both untreated morbidityand hospital utilisation has been somewhat sharper for men, eventhough they continue in absolute terms to be better off than poorwomen (Sen et al. 2002b).

Recent work by Gwatkin and Guillot (2000) points out that amongthe poorest 20 per cent of people in the world communicable, maternal,perinatal nutritional conditions are responsible for a relatively largerproportion of female than male ill health (7.5 per cent more deaths,11.4 per cent more disability life adjusted years [DALYs~. When mater-nal conditions are excluded from this calculation, the higher levels offemale ill-health still persist (6.3 per cent more deaths, 7.5 per centmore DALYs). Interestingly, the report also shows that where previ-ously at an aggregate level men were seen to suffer more from non-communicable diseases than women, when cross-cut by class, it is richwomen who suffer from more non-communicable diseases (5.4 percent more deaths, 7.8 per cent more DALYs). These results clearlyindicate the need for further investigation into the links betweenpoverty and gender equity in health.

Given the unequal nature of gender relations, a gendered approachoften tends to uncover health inequity as it particularly affects women.But gender can also work to men’s disadvantage in health.

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Relative Vulnerabilities and the’Gender Paradox’ in Health

Poorer male health outcomes in higher-income countries seem to belinked to behaviours like smoking, heavy drinking, violence and risk-taking in traffic or sports. These gendered influences on male mortalityand morbidity show strong socio-economic class determinants. Lower-class Dutch males aged 15 to 24 were three times more likely thanhigher-class males of the same age to have a trauma diagnosis (Gijsbersvan Wijk et al. 1995).An equally dramatic example is that of male life expectancy in Russia.

Between 1989 and 1994, life expectancy at birth decreased by 6.5 yearsfor men and 3.5. years for women due to a striking increase in adultmortality. In 1994 women in Russia could expect to live 13.5 yearslonger than men (Shkolnikov 1997). A substantial part of this gendergap reflects extraordinary pressures from a rapidly changing society,particularly on the disadvantaged. Recent research details that althoughmortality rates have remained lower among women than men, womenof lower social status have suffered disproportionately (Chenet 2000).More research is needed to explain how men and women from differentclasses react differently to dynamic changes in society.Moving beyond mortality, considerable attention has focused on

the gender paradox in health in the US and in Western Europe. Womenreport more physical and psychological symptoms, more chronicillness, more disability, use more medication and visit physicians moreoften. In contrast, men suffer more from life-threatening diseases andthese cause more permanent disability and earlier death (Nathansonand Lopez 1987; Verbrugge 1976). Although higher rates of male mor-tality tend to capture the public imagination, the larger burden offemale morbidity is less spectacular and hence less in the public eyes(Verbrugge 1985). To put it more bluntly, men die of their illnesseswhile women have to live with theirs (Thorslund et al. 1993).

Conventional wisdom attributes women’s worse morbidity statusto their reproductive health needs. In low-income countries repro-ductive health problems may play a large role in explaining overallgender differences in health and women may have less access to healthcare services (Puentes-Markides 1992; Vlassoff 1994). However, a Dutchstudy showed that 60 per cent of women’s health problems are notcaused by reproductive morbidity (Gijsbers van Wijk et at. 1996). Even

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though reproductive health issues account for some of the female excessin morbidity, women who do not report reproductive health problemsstill report worse health than men (Popay et al. 1993).Women’s higher morbidity has also been hypothesised as being

caused by their greater sensitivity to bodily cues and to the socialacceptability of sick roles for women. It has been suggested that womenpresent more vague symptoms, which doctors tend to label as beingpsychiatric because they are unable to always diagnose disease.However, one study found that doctors’ reporting of primary healthcare patients showed that less than 20 per cent of women’s healthproblems were due to symptoms without diagnosable disease. Moreoverthe study found few sex differences with this category, svggesting thatwomen do not have lower thresholds for perceiving and reportingsymptoms (Gijsbers van Wijk et al. 1995). Another study found thatwomen did report more ’sick building symptoms’ than men did, butthat clinical examinations revealed this excess prevalence to be realrather than a reporting artefact (Stenberg and Wall 1995).Women have been shown to use more medication and health services

than men. A large part of this pattern can be attributed to women’suse of preventive health services for contraceptives, cervical screeningand other diagnostic tests (Gijsbers van Wijk et al. 1995). This maycontribute to women’s higher chronic morbidity, as their preventivecare may diminish the severity of their health problems. Decliningmortality rates coupled with earlier medical diagnosis of chronic diseasehas led to ill people living longer. As a result the ongoing managementof health problems rather than their cure has become the health realityfor many elderly. Considering that women constitute the majority ofthe elderly, these trends are especially important for women (Verbrugge1985).’Some researchers are sceptical about the uniformity of the gender

paradox in health. Although they find a general pattern of higher femalemorbidity, some authors note the lack of predicted female excess inspecific instances (Kandrack et al. 1991).

[The] direction and magnitude of sex differences in health varyaccording to the particular symptom or condition in question andaccording to the phase of the life cycle. Female excess is onlyconsistently found across the life span for psychological distress and

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is far less apparent, or reversed, for a number of physical symptomsand condition. (Macintyre et al. 1996)

Moreover the conclusions one draws often depend heavily on the typeof health measure used (Arber 1997).

Such evidence and the questions they spur underlines the cautionwith which generalisations about gender differences in health can bemade and the importance of finding the underlying causes that explainthem. Higher male mortality is not universal and is qualified by povertyin ways that are not yet well understood in some countries. Higher fe-male morbidity may also not have uniform or universal explanationswithin and across societies. Both phenomena need more careful examin-ation. In particular, both female and male vulnerability need to becontextualised if we are to understand better which social environments

prove harmful to their health.

Engendering Health Research

Data

A cautious interpretation of standard statistics and variables used inhealth research is recommended. As Macintyre (1986) puts it, ’Noneof the social positions of interest, or the variables used to representthem, are unproblematic or self-evident in their meaning, measurementor significance.’ For example, men have higher rates of substance abusedisorders and women have higher rates of affective disorders. However,biases in social norms exaggerate these differences as men are moreaverse to a ’psychiatric label’, while women are more averse to a ’drinkerlabel’ (Allen et al. 1998, cited in Astbury 2002). Where social norms ofwomen ’suffering silently’ prevail, morbidity data are well known tobe underestimated, especially in areas with high levels of social stigma,like, for example, violence against women, abortions and vesico-vaginalfistulae.

Unfortunately, the absence of gender perspectives is also felt insimpler and rather pervasive ways. This includes the fact that healthdata are still not systematically desegregated by sex, let alone presentedin a manner that will allow comparisons with other social stratifiers

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such as socio-economic class, race or caste. Without appropriate sex-desegregated data, it is difficult even to begin a gendered analysis.

Gender-sensitive Methodologies ,

Health research methodologies have been challenged to respond tohealth equity in general and gender in particular (Hanson 2002). Forexample, gender differences in malaria prevalence vary depending onthe study design used. Data derived from clinics in Thailand indicateda male female ratio of 6:1, while mobile clinics found a ratio of 4:1.

Considering women’s greater use of pharmacies and traditional healers,this statistic would most likely narrow even further if a survey basedon all providers or a population-based survey were to be carried out(Ettling et al. 1989). Within the global burden of disease methodology,rankings by ’experts’ of different kinds of female morbidity have beenfound to be significantly at odds with those of women from poorcommunities (Sadana 1998).

Apart from questioning study design and methodology, researchersalso need to be careful about how variables are defined and measured.With respect to gender and social class, researchers are beginning toquestion the validity of assuming that husband’s income levels can besurrogates for their wives’ social class (Arber 1997). Yet, male standardscontinue to prevail. In Sweden the currently used occupational clas-sification scheme, developed for men, differentiates poorly betweenwomen’s jobs. Highly qualified and specialised secretarial work is thusfound under the same occupational code as general office duties androutine typing. These crude measures of social position may be con-tributing to the weaker class gradients found in women’s as comparedto men’s health (ostlin 2002).

Variables commonly used to measure race, income and gender maystill not be adequately sensitive to reveal all the mechanisms of socialdiscrimination in health. For example, how people respond to dis-crimination may affect their health (Krieger 1990). Black women whoresponded actively to unfair treatment were less likely to report highblood pressure than women who internalised their responses. Interest-

ingly, black women who reported no experiences of racial discrimin-ation were at highest risk for hypertension. Researchers are alsoexploring the effects of race and anti-gay discrimination on health(Krieger and Sidney 1997).

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These examples show the limitations and biases of current variablesand methodologies, and the need to proceed cautiously. In formulatingresearch questions and hypotheses it is certainly easier to move forwardin areas where biology is unlikely to play a role. However, where itdoes play a role, a simple but useful guideline is for the researcher tonot assume that biology accounts for all or even the bulk of the differ-ences between women and men. Gendered differences in economicaccess, social power and behavioural norms must be presumed tooperate unless proven otherwise. As stated before, the pathways canbe complex and interactive, but they can certainly be investigated sys-tematically.

Bias in Clinical and Drugs Research

Health problems that specifically or predominantly affect women havereceived less attention and funds than those mainly prevalent amongmen. The lack of research is obvious in areas concerning the menstrualcycle and non-lethal chronic diseases that affect women dispropor-tionately, such as rheumatism, fibromyalgia and chronic fatigue syn-drome (Doyal 1995; Goldman and Hatch 2000). The only exceptionto this general trend is the area of contraceptive research, which hashistorically neglected male methods.When women have been considered, two polar extremes tend to

emerge. Either their biological specificity is not noted at all or onlytheir reproductive potential is focussed upon (Silbergeld 2000). Forexample, regulations against lead only provide protection for womenof reproductive age (Hansson 1998). This ignores health risks to womenwho are not of reproductive age as well as health risks (reproductiveor otherwise) to men.An even more serious problem regarding medical and drug research

has been the exclusion of female subjects from study populations. Thereason for omitting female subjects from research is that the menstrualcycle introduces a potentially confounding variable. Additional groundsfor excluding women of childbearing age are the fears that experimentaltreatments or drugs may affect their fertility. Experimental use of treat-ment might, moreover, expose foetuses to unknown risk. More atten-tion needs to be paid to the implications of non-reproductive biologicaldifferences of women from men in this field. Evidence shows thatwomen have a higher proportion of fat tissue, causing greater risk

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from fat soluble chemicals, as well as thinner skin and slower meta-bolism causing differential rates of absorption, metabolism andexcretion of chemicals (bstlin 2002; Sims and Butter 2002).

Nonetheless, consequences for women of extending research resultsbased on male models without convincing evidence of their applicabilityto women continue to be harmful (Hammarstr6m et al. 2001). Evidencehas accumulated showing that guidelines for diagnoses, treatment andrehabilitation are not adapted to the specific needs of women in general,let alone to women from different class and social backgrounds. TheAmerican Psychiatric Associations’s Diagnostic and Statistical Manualof Mental Disorders (DSM III) defined the criteria for diagnosingschizophrenia-based on male symptoms. Application of these criteriato WHO data led to the exclusion of 5 per cent and as much as 12 percent women who actually had schizophrenia (Hambrecht et al. 1992,cited in Astbury 2002).

Research on gender differences in cardiovascular epidemiology hasrevealed serious consequences from applying ’male-based’ diagnostictechniques and treatments on female patients (Gijsbers van Wijk et al.1996). Medical textbooks seldom highlight the obvious gender differ-ences regarding the symptomatology of heart attack. It is not surprising,therefore, that for female patients arriving at emergency rooms, thediagnostic procedure takes longer than for men. This is mainly becausedoctors, more familiar with male symptomatology, do not immediatelyrecognise the symptoms female patients with heart attack may have.To counter such biases researchers need to involve research subjects,

not only at the time of interpreting and understanding research results,but at the early stage of research design, when shaping and refiningquestions and hypotheses. If this had been done in acceptability studiesof intrauterine contraceptive devices in poor populations, for instance,perhaps the wide prevalence of reproductive tract infections wouldhave been detected sooner.

Clearly, much needs to be done to remove inadvertent and/or inten-tional gender bias in health research. As long as women in general, andfeminist health researchers and decision-makers in particular, are inthe minority and are less powerful, we will need to build in safeguardsto ensure that gender equity is addressed. Such efforts based on a humanrights framework for gender equity must acknowledge the need tocounteract bias, recognise gender-differentiated needs, and be com-mitted to protect and promote rights to health for all.

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Notes

1. For a more extensive review please refer to Sen et al. 2002a.2. Gender refers to the social distinctions between women and men due to unequal

power relations, leading to differences in access to resources, divisions of labour,hierarchies of decision making and socially sanctioned discriminatory norms.

3. The infiltration of discriminatory gender norms into medical knowledge is not,however, a Western monopoly. Much more research is needed to explore how tradi-tional medical systems treat gender.

4. It is important to note that women of colour or from lower classes or castes weretraditionally excluded from such paternalistic concerns about their biological frailty(Krieger and Fee 1994).

5. In this paper we use the terms ’gender equity’ and ’gender justice’ interchangeably.6. For example, similar death rates from coronary heart disease for women and men,

despite women’s supposed protection from higher levels of oestrogen (McKinlay1996), may well indicate the presence of counteracting social disadvantage.

7. Initial research across a range of countries seems to prove a female excess in morbidityeven after controlling for female advantage in longevity (Rahman et al. 1994).

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Gita Sen is Sir Ratan Tata Chair Professor, Indian Institute of Management (IIM)Bangalore, Bannerghatta Road, Bangalore 560 076, India.

Asha George is Project Investigator, IIM Bangalore, India.Piroska Östlin is Research Manager, National Institute of Public Health, Research

Department, 103 52 Stockholm, Sweden.