Sex bias in infectious disease epidemiology: patterns and processes

Abstract

Background: Infectious disease incidence is often male-biased. Two main hypotheses have been proposed to explain this observation. The physiological hypothesis (PH) emphasizes differences in sex hormones and genetic architecture, while the behavioral hypothesis (BH) stresses gender-related differences in exposure. Surprisingly, the population-level predictions of these hypotheses are yet to be thoroughly tested in humans.

Methods and findings: For ten major pathogens, we tested PH and BH predictions about incidence and exposure-prevalence patterns. Compulsory-notification records (Brazil, 2006-2009) were used to estimate age-stratified ♂:♀ incidence rate ratios for the general population and across selected sociological contrasts. Exposure-prevalence odds ratios were derived from 82 published surveys. We estimated summary effect-size measures using random-effects models; our analyses encompass ∼0.5 million cases of disease or exposure. We found that, after puberty, disease incidence is male-biased in cutaneous and visceral leishmaniasis, schistosomiasis, pulmonary tuberculosis, leptospirosis, meningococcal meningitis, and hepatitis A. Severe dengue is female-biased, and no clear pattern is evident for typhoid fever. In leprosy, milder tuberculoid forms are female-biased, whereas more severe lepromatous forms are male-biased. For most diseases, male bias emerges also during infancy, when behavior is unbiased but sex steroid levels transiently rise. Behavioral factors likely modulate male-female differences in some diseases (the leishmaniases, tuberculosis, leptospirosis, or schistosomiasis) and age classes; however, average exposure-prevalence is significantly sex-biased only for Schistosoma and Leptospira.

Conclusions: Our results closely match some key PH predictions and contradict some crucial BH predictions, suggesting that gender-specific behavior plays an overall secondary role in generating sex bias. Physiological differences, including the crosstalk between sex hormones and immune effectors, thus emerge as the main candidate drivers of gender differences in infectious disease susceptibility.

Figure 1. Infectious disease incidence in Brazil: sex- and age class-stratified incidence profiles (cases/100,000 population).

Diseases: American cutaneous (CL) and visceral leishmaniasis (VL); schistosomiasis (SCH); pulmonary tuberculosis (TB); lepromatous leprosy (LL); tuberculoid leprosy (TL); typhoid fever (TF); leptospirosis (LE); meningococcal meningitis (MM); hepatitis A (HA); and severe dengue fever (SDF). Incidence (2006–2009) was computed from Brazilian compulsory-notification records and official demographic data for males (M, blue lines) and females (F, orange-red lines). Age classes (in years) are given on the x axes. Insets present overall annual incidence for 2006–2009 (blue, males; orange, females). See main text and Dataset S1 for details.

Figure 2. Infectious disease incidence in Brazil: male:female incidence rate ratios (IRRs) and 95% confidence intervals (CIs) computed from compulsory-notification records and official demographic data.

Diseases: American cutaneous (CL) and visceral leishmaniasis (VL); schistosomiasis (SCH); pulmonary tuberculosis (TB); lepromatous leprosy (LL); tuberculoid leprosy (TL); typhoid fever (TF); leptospirosis (LE); meningococcal meningitis (MM); hepatitis A (HA); and severe dengue fever (SDF). Circles are random-effects point estimates computed from Brazilian compulsory-notification annual incidence records (2006–2009). IRR >1 indicates male-biased incidence; the vertical line at IRR = 1 indicates no sex bias. When CIs include 1, sex bias is not statistically significant at the 5% level. Age classes are given on the y axes; a few IRRs could not be estimated due to small numbers of incident cases. The last Panel (labeled ‘Infants’) compares cumulative incidence (2006–2009) among infants (<1 year old); despite the likely absence of sex-related behavior/exposure differences, significant male bias is seen in several diseases. See main text and Dataset S1 for details.

Figure 3. Infectious disease incidence in Brazil: sociological contrasts.

Panels A-E: rural and urban male:female incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for American cutaneous leishmaniasis in Brazilian sub-regions where Leishmania braziliensis (Panel A) or Le. guyanensis (Panel B) are the primary etiological agent; American visceral leishmaniasis (Panel C); schistosomiasis (Panel D); and leptospirosis (Panel E). Each age class (y axes) is represented by a gray or white band, with rural and urban estimates given as the upper and lower value within each band (as illustrated for infants under 1 year of age in Panel A); IRR >1 indicates male-biased incidence; the vertical line at IRR = 1 indicates no sex bias; when CIs include 1, sex bias is not statistically significant at the 5% level. Panel F: percentage of males (with 95%CIs) among 9498 incident leptospirosis cases (Brazil, 2006–2010); for each age class (grey/white band), the overall value is followed by infection site-specific estimates for the home (all age classes) and work environments (age classes >10); the vertical line at 50% indicates even demographic sex ratios. IRRs and CIs were computed from compulsory-notification records and official demographic data. See main text and Dataset S2 for details.

Figure 4. Sex bias in exposure to human pathogens: published exposure-without-disease surveys.

The data reveal no sex bias for Leishmania spp. (CL, cutaneous forms; VL, visceral forms); Mycobacterium leprae (LEP); Salmonella enterica serovar Typhi (TF); Hepatitis A virus (HA); Dengue virus (DEN); or Mycobacterium tuberculosis (TB). Exposure to Schistosoma mansoni (SCH 1, as determined by the Kato-Katz technique; SCH 2, as determined by immunological tests); and Leptospira interrogans (LE) is male-biased. Neisseria meningitidis (MM) is more often carried by adult men, likely because of male-biased risk factors such as smoking; MM 2 is a subset analysis of surveys involving children or high-school students, which reveals no sex bias; furthermore, many papers reporting a “non-significant” gender difference do not present the actual figures. Estimates (x axis) are random-effects odds ratios with 95% confidence intervals; when these include 1, sex bias is not statistically significant at the 5% level. The numbers of individual tests and published studies (in parentheses) analyzed are also given to the right of each estimate.