In the stereotypical Ozzie and Harriet family of the 1950s, men ruled the roost while women ruled the roast. That's no longer true (if it ever was), but in most households women are still in charge of nutrition. They stock the pantry, plan the menus, and fill the plates. In most households it's a good thing, since the average woman knows more about nutrition than the average man. But when it comes to optimal nutrition, there are differences between the sexes. The differences are subtle, but they may affect a man's health.
Breast cancer is the second most common cancer in the world and the most common among women. It is also among the ten most common chronic diseases of women, and a substantial contributor to loss of quality of life (Gronowski and Schindler, Table IV).[6] Globally, it accounts for 25% of all cancers. In 2016, breast cancer is the most common cancer diagnosed among women in both developed and developing countries, accounting for nearly 30% of all cases, and worldwide accounts for one and a half million cases and over half a million deaths, being the fifth most common cause of cancer death overall and the second in developed regions. Geographic variation in incidence is the opposite of that of cervical cancer, being highest in Northern America and lowest in Eastern and Middle Africa, but mortality rates are relatively constant, resulting in a wide variance in case mortality, ranging from 25% in developed regions to 37% in developing regions, and with 62% of deaths occurring in developing countries.[17][122]
Systematically report and evaluate women's nutrition outcomes in research and program evaluation documents in low- and middle-income countries, including outcomes for adolescents, older women, and mothers (as opposed to reporting on women's nutrition as child nutrition outcomes alone). When possible, report and evaluate differences by setting (e.g., rural compared with urban) and socioeconomic status.
  Community centers  ↑ MN provision, ↑ health care utilization, ↑ knowledge about FP, ↑/NC use of FP  ↑ MN provision, ↑ health care utilization, ↑ knowledge about FP, ↑/NC use of FP  ↑ knowledge about nutritional needs, ↑ MN provision, ↓/NC maternal mortality, ↓ parasitemia, ↑ health care utilization, ↑ hospital deliveries, ↑ knowledge about FP, ↑/NC use of FP, ↑ STI testing   
The effect of education programs on nutrition outcomes is difficult to assess because programs often have poor baseline data or nutrition outcomes are not evaluated (174, 182). Studies that used longitudinal analyses and “natural” experiments (e.g., before and after a national education policy) found that education was associated with reduced fertility (183, 184), and delayed early marriages and pregnancies (184–187). The impact was more significant for higher levels of education (185). However, 1 study in Malawi identified negative associations between education and timing of first birth, although these findings were largely not statistically significant (188). Secondary education for adolescents and women of reproductive age also showed no impact on women's empowerment (184), although it did show an impact on improved literacy and leadership (174). Educational interventions that provided conditional cash transfers (CCTs) and school feeding, as well as other forms of social protection to families of enrolled girls, were associated with greater school enrollment and attendance (189–191), improved test scores (189, 190), reduced gender gaps (192), and reduced hunger (190, 191).
^ Jump up to: a b c Aldridge, Robert W.; Story, Alistair; Hwang, Stephen W.; Nordentoft, Merete; Luchenski, Serena A.; Hartwell, Greg; Tweed, Emily J.; Lewer, Dan; Vittal Katikireddi, Srinivasa (2017-11-10). "Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis". Lancet. 391 (10117): 241–250. doi:10.1016/S0140-6736(17)31869-X. ISSN 1474-547X. PMC 5803132. PMID 29137869. All-cause standardised mortality ratios were significantly increased in 91 (99%) of 92 extracted datapoints and were 11·86 (95% CI 10·42–13·30; I2=94·1%) in female individuals
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