Commercials, careers and culture: travelling salesmen in Britain 1890s-1930s

Within the lower middle-class, British commercial travellers established a strong fraternal culture before 1914. This article examines their interwar experiences in terms of income, careers, and associational culture. It demonstrates how internal labour markets operated, identifies the ways in which commercial travellers interpreted their role, and explores their social and political attitudes

Enhancing the early student experience

This paper is concerned with identifying how the early student experience can be enhanced in order to improve levels of student retention and achievement. The early student experience is the focus of this project as the literature has consistently declared the first year to be the most critical in shaping persistence decisions. Programme managers of courses with high and low retention rates have been interviewed to identify activities that appear to be associated with good retention rates. The results show that there are similarities in the way programmes with high retention are run, with these features not being prevalent on programmes with low retention. Recommendations of activities that appear likely to enhance the early student experience are provided

Height and risk of death among men and women: aetiological implications of associations with cardiorespiratory disease and cancer mortality

OBJECTIVES: Height is inversely associated with cardiovascular disease mortality risk and has shown variable associations with cancer incidence and mortality. The interpretation of findings from previous studies has been constrained by data limitations. Associations between height and specific causes of death were investigated in a large general population cohort of men and women from the West of Scotland. DESIGN: Prospective observational study. SETTING: Renfrew and Paisley, in the West of Scotland. SUBJECTS: 7052 men and 8354 women aged 45-64 were recruited into a study in Renfrew and Paisley, in the West of Scotland, between 1972 and 1976. Detailed assessments of cardiovascular disease risk factors, morbidity and socioeconomic circumstances were made at baseline. MAIN OUTCOME MEASURES: Deaths during 20 years of follow up classified into specific causes. RESULTS: Over the follow up period 3347 men and 2638 women died. Height is inversely associated with all cause, coronary heart disease, stroke, and respiratory disease mortality among men and women. Adjustment for socioeconomic position and cardiovascular risk factors had little influence on these associations. Height is strongly associated with forced expiratory volume in one second (FEV1) and adjustment for FEV1 considerably attenuated the association between height and cardiorespiratory mortality. Smoking related cancer mortality is not associated with height. The risk of deaths from cancer unrelated to smoking tended to increase with height, particularly for haematopoietic, colorectal and prostate cancers. Stomach cancer mortality was inversely associated with height. Adjustment for socioeconomic position had little influence on these associations. CONCLUSION: Height serves partly as an indicator of socioeconomic circumstances and nutritional status in childhood and this may underlie the inverse associations between height and adulthood cardiorespiratory mortality. Much of the association between height and cardiorespiratory mortality was accounted for by lung function, which is also partly determined by exposures acting in childhood. The inverse association between height and stomach cancer mortality probably reflects Helicobacter pylori infection in childhood resulting inor being associated withshorter height. The positive associations between height and several cancers unrelated to smoking could reflect the influence of calorie intake during childhood on the risk of these cancers

Disability and participation in breast and bowel cancer screening in England: a large prospective study

Background: There is limited information about participation in organised population-wide screening programmes by people with disabilities. Methods: Data from the National Health Service routine screening programmes in England were linked to information on disability reported by the Million Women Study cohort participants. Results: Of the 473 185 women offered routine breast or bowel cancer screening, 23% reported some disability. Women with disabilities were less likely than other women to participate in breast cancer screening (RR=0.64, 95% CI: 0.62–0.65) and in bowel cancer screening (RR=0.75, 0.73–0.76). Difficulties with self-care or vision were associated with the greatest reduction in screening participation. Conclusion: Participation in routine cancer screening programmes in England is reduced in people with disabilities and participation varies by type of disability

Cognitive and social activities and long-term dementia risk: the prospective UK Million Women Study

BACKGROUND: Although dementia is associated with non-participation in cognitive and social activities, this association might merely reflect the consequences of dementia, rather than any direct effect of non-participation on the subsequent incidence of dementia. Because of the slowness with which dementia can develop, unbiased assessment of any such direct effects must relate non-participation in such activities to dementia detection rates many years later. Prospective studies with long-term follow-up can help achieve this by analysing separately the first and second decade of follow-up. We report such analyses of a large, 20-year study. METHODS: The UK Million Women Study is a population-based prospective study of 1·3 million women invited for National Health Service (NHS) breast cancer screening in median year 1998 (IQR 1997-1999). In median year 2001 (IQR 2001-2003), women were asked about participation in adult education, groups for art, craft, or music, and voluntary work, and in median year 2006 (IQR 2006-2006), they were asked about reading. All participants were followed up through electronic linkage to NHS records of hospital admission with mention of dementia, the first mention of which was the main outcome. Comparing non-participation with participation in a particular activity, we used Cox regression to assess fully adjusted dementia risk ratios (RRs) during 0-4, 5-9, and 10 or more years, after information on that activity was obtained. FINDINGS: In 2001, 851 307 women with a mean age of 60 years (SD 5) provided information on participation in adult education, groups for art, craft, or music, and voluntary work. After 10 years, only 9591 (1%) had been lost to follow-up and 789 339 (93%) remained alive with no recorded dementia. Follow-up was for a mean of 16 years (SD 3), during which 31 187 (4%) had at least one hospital admission with mention of dementia, including 25 636 (3%) with a hospital admission with dementia mentioned for the first time 10 years or more after follow-up began. Non-participation in cognitive or social activities was associated with higher relative risks of dementia detection only during the first decade after participation was recorded. During the second decade, there was little association. This was true for non-participation in adult education (RR 1·04, 99% CI 0·98-1·09), in groups for art, craft, or music (RR 1·04, 0·99-1·09), in voluntary work (RR 0·96, 0·92-1·00), or in any of these three (RR 0·99, 0·95-1·03). In 2006, 655 118 women provided information on reading. For non-reading versus any reading, there were similar associations with dementia, again with strong attenuation over time since reading was recorded, but longer follow-up is needed to assess this reliably. INTERPRETATION: Life has to be lived forwards, but can be understood only backwards. Long before dementia is diagnosed, there is a progressive reduction in various mental and physical activities, but this is chiefly because its gradual onset causes inactivity and not because inactivity causes dementia. FUNDING: UK Medical Research Council, Cancer Research UK

A Secular Trend toward Earlier Male Sexual Maturity: Evidence from Shifting Ages of Male Young Adult Mortality

This paper shows new evidence of a steady long-term decline in age of male sexual maturity since at least the mid-eighteenth century. A method for measuring the timing of male maturity is developed based on the age at which male young adult mortality accelerates. The method is applied to mortality data from Sweden, Denmark, Norway, the United Kingdom, and Italy. The secular trend toward earlier male sexual maturity parallels the trend toward earlier menarche for females, suggesting that common environmental cues influence the speed of both males' and females' sexual maturation

Infant mortality and isotopic complexity: new approaches to stress, maternal health, and weaning

Objectives: Studies of the carbon and nitrogen stable isotope ratios (δ13C and δ15N) of modern tissues with a fast turnover, such as hair and fingernails, have established the relationship between these values in mothers and their infants during breastfeeding and weaning. Using collagen from high-resolution dentine sections of teeth, which form in the perinatal period we investigate the relationship between diet and physiology in this pivotal stage of life. Materials and Methods: Childhood dentine collagen δ13C and δ15N profiles were produced from horizontal sections of permanent and deciduous teeth following the direction of development. These were from two 19th-century sites (n = 24) and a small number (n = 5) of prehistoric samples from Great Britain and Ireland. Results: These high-resolution data exhibit marked differences between those who survived childhood and those who did not, the former varying little and the latter fluctuating widely. Discussion: Breastfeeding and weaning behavior have a significant impact on the morbidity and mortality of infants and the adults they become. In the absence of documentary evidence, archaeological studies of bone collagen of adults and juveniles have been used to infer the prevalence and duration of breastfeeding. These interpretations rely on certain assumptions about the relationship between isotope ratios in the bone collagen of the adult females and the infants who have died. The data from this study suggest a more complex situation than previously proposed and the potential for a new approach to the study of maternal and infant health in past populations

Methods and participant characteristics in the Cancer Risk in Vegetarians Consortium: a cross-sectional analysis across 11 prospective studies

\ua9 The Author(s) 2024. Background: The associations of vegetarian diets with risks for site-specific cancers have not been estimated reliably due to the low number of vegetarians in previous studies. Therefore, the Cancer Risk in Vegetarians Consortium was established. The aim is to describe and compare the baseline characteristics between non-vegetarian and vegetarian diet groups and between the collaborating studies. Methods: We harmonised individual-level data from 11 prospective cohort studies from Western Europe, North America, South Asia and East Asia. Comparisons of food intakes, sociodemographic and lifestyle factors were made between diet groups and between cohorts using descriptive statistics. Results: 2.3 million participants were included; 66% women and 34% men, with mean ages at recruitment of 57 (SD: 7.8) and 57 (8.6) years, respectively. There were 2.1 million meat eaters, 60,903 poultry eaters, 44,780 pescatarians, 81,165 vegetarians, and 14,167 vegans. Food intake differences between the diet groups varied across the cohorts; for example, fruit and vegetable intakes were generally higher in vegetarians than in meat eaters in all the cohorts except in China. BMI was generally lower in vegetarians, particularly vegans, except for the cohorts in India and China. In general, but with some exceptions, vegetarians were also more likely to be highly educated and physically active and less likely to smoke. In the available resurveys, stability of diet groups was high in all the cohorts except in China. Conclusions: Food intakes and lifestyle factors of both non-vegetarians and vegetarians varied markedly across the individual cohorts, which may be due to differences in both culture and socioeconomic status, as well as differences in questionnaire design. Therefore, care is needed in the interpretation of the impacts of vegetarian diets on cancer risk

Correction to: Methods and participant characteristics in the Cancer Risk in Vegetarians Consortium: a cross-sectional analysis across 11 prospective studies (BMC Public Health, (2024), 24, 1, (2095), 10.1186/s12889-024-19209-y)

\ua9 The Author(s) 2025. Following publication of the original article [1], the authors identified an error in Table 6 and Table S5. The percentage for the every used oral contraceptives value for the NIH-AARP study has been corrected to 39%. Women-specific characteristics by cohort (n = 1,546,217)1 Cohort Age at menarche ≤ 12 years Parous Age at first birth ≥ 25 years Postmenopausal Age at menopause ≥ 50 years2 Ever used oral contraceptive Ever used HRT Adventist Health Study-2 51.4 83.1 31.7 77.0 64.5 58.8 39.4 CARRS-1 12.2 94.1 - 36.9 19.7 3.5 - CARRS-2 12.9 93.8 - 41.9 23.4 6.9 EPIC-Oxford 39.8 61.0 38.2 40.2 54.8 73.7 18.2 Oxford Vegetarian Study - 47.5 29.4 26.6 - 55.3 - Tzu Chi Health Study 8.6 91.8 - 63.0 54.2 15.7 19.6 UK Women’s Cohort Study 41.6 77.2 44.8 60.9 48.0 66.9 27.2 China Kadoorie Biobank 5.5 98.7 32.5 57.2 43.1 9.8 - Million Women Study 38.8 88.4 36.4 100 56.8 61.3 53.4 NIH-AARP 48.6 83.7 23.5 100 39.6 39.0 52.9 UK Biobank 37.6 81.2 47.1 77.8 63.3 81.1 37.7 33.5 87.3 35.3 84.2 52.1 50.6 37.8 Abbreviations: CARRS, Centre for cArdiometabolic Risk Reduction in South Asia; HRT, hormone replacement therapy; EPIC, European Prospective Investigation into Cancer and Nutrition; NIH-AARP, National Institutes of Health-AARP Diet and Health Study. 1Values are % of women within cohort. 2Postmenopausal women only. “-” indicates that no information was available for this variable in the specified cohort. Baseline characteristics of women by cohort1 Total AHS-2 CARRS-1 CARRS-2 EPIC-Oxford OVS TCHS UKWCS CKB MWS NIH-AARP UK Biobank N 1,546,217 42,194 6,372 5,065 41,335 6,480 3,329 30,148 300,909 639,026 215,905 255,454 Living with partner Yes 1,145,967 (74.1) 27,503 (65.2) 5,671 (89.0) 4,332 (85.5) 27,614 (66.8) 3,497 (54.0) 2824 (84.8) 22,282 (73.9) 267,799 (89.0) 511,789 (80.1) 95,749 (44.3) 176,907 (69.3) No 336,711 (21.8) 13,937 (33.0) 701 (11.0) 733 (14.5) 13,649 (33.0) 2,934 (45.3) 504 (15.1) 7,415 (24.6) 33,110 (11.0) 118,337 (18.5) 118,140 (54.7) 27,251 (10.7) Unknown 63,539 (4.1) 754 (1.8) 0 (0.00) 0 (0.00) 72 (0.17) 49 (0.76) 1 (0.00) 451 (1.5) 0 (0.00) 8,900 (1.4) 2,016 (0.93) 51,296 (20.1) Educational status Less than secondary/high school 514,795 (33.3) 3,052 (7.2) 1,568 (24.6) 1,271 (25.1) 5,426 (13.1) 309 (4.8) 1023 (30.7) 4,671 (15.5) 170,715 (56.7) 217,050 (34.0) 67,342 (31.2) 42,368 (16.6) Secondary/high school or equivalent 572,012 (37.0) 18,125 (43.0) 3,859 (60.6) 2,908 (57.4) 16,422 (39.7) 4,573 (70.6) 1636 (49.1) 15,539 (51.5) 116,872 (38.8) 305,150 (47.8) 22,927 (10.6) 64,001 (25.1) University degree or equivalent 430,226 (27.8) 20,431 (48.4) 945 (14.8) 884 (17.5) 16,406 (39.7) 434 (6.7) 670 (20.1) 7,372 (24.5) 13,322 (4.4) 106,496 (16.7) 118,637 (54.9) 144,629 (56.6) Unknown 29,184 (1.9) 586 (1.4) 0 (0.00) 2 (0.04) 3,081 (7.5) 1,164 (18.0) 0 (0.00) 2,566 (8.5) 0 (0.00) 10,330 (1.6) 6,999 (3.2) 4,456 (1.7) Cigarette smoking Never 974,560 (63.0) 35,304 (83.7) 6,094 (95.6) 4,985 (98.4) 25,457 (61.6) 3,595 (55.5) 3274 (98.3) 16,851 (55.9) 285,673 (94.9) 346,928 (54.3) 94,000 (43.5) 152,399 (59.7) Previous 406,326 (26.3) 6,166 (14.6) 5 (0.08) 21 (0.41) 11,253 (27.2) 1,809 (27.9) 40 (1.20) 9,148 (30.3) 2,619 (0.87) 211,953 (33.2) 84,058 (38.9) 79,254 (31.0) Current 146,379 (9.5) 410 (0.97) 58 (0.91) 59 (1.2) 4,439 (10.7) 1,049 (16.2) 15 (0.45) 3,224 (10.7) 12,617 (4.2) 71,277 (11.2) 30,343 (14.1) 22,888 (9.0) Unknown 18,952 (1.2) 314 (0.74) 215 (3.4) 0 (0.00) 186 (0.45) 27 (0.42) 0 (0.00) 925 (3.1) 0 (0.00) 8,868 (1.4) 7,504 (3.5) 913 (0.36) Physical activity Inactive 357,643 (23.1) 8,553 (20.3) 2,681 (42.1) 3,815 (75.3) 23,253 (56.3) 2,596 (40.1) 1248 (37.5) 22,033 (73.1) 99,953 (33.2)2 36,813 (5.8) 79,280 (36.7) 77,418 (30.3) Moderately active 426,785 (27.6) 13,711 (32.5) 797 (12.5) 491 (9.7) 6,931 (16.8) 1,871 (28.9) 1082 (32.5) 7,074 (23.5) 100,654 (33.4)2 70,898 (11.1) 99,164 (45.9) 124,112 (48.6) Highly active 570,911 (36.9) 17,753 (42.1) 1,494 (23.4) 40 (0.79) 4,770 (11.5) 1,831 (28.3) 999 (30.0) 1,032 (3.4) 100,302 (33.3)2 364,921 (57.1) 34,746 (16.1) 43,023 (16.8) Unknown 190,878 (12.3) 2,177 (5.2) 1,400 (22.0) 719 (14.2) 6,381 (15.4) 182 (2.8) 0 (0.00) 9 (0.03) 0 (0.00) 166,394 (26.0) 2,715 (1.3) 10,901 (4.3) History of diabetes Yes 71,748 (4.6) 3,195 (7.6) 777 (12.2) 830 (16.4) 459 (1.1) 33 (0.51) 155 (4.7) 544 (1.8) 18,426 (6.1) 21,570 (3.4) 16,204 (7.5) 9,555 (3.7) No 1,466,761 (94.9) 38,512 (91.3) 5,569 (87.4) 4,231 (83.5) 36,684 (88.7) 6,419 (99.1) 3174 (95.3) 27,293 (90.5) 282,483 (93.9) 617,456 (96.6) 199,701 (92.5) 245,239 (96.0) Unknown 7,708 (0.50) 487 (1.2) 26 (0.41) 4 (0.08) 4,192 (10.1) 28 (0.43) 0 (0.00) 2,311 (7.7) 0 (0.00) 0 (0.00) 0 (0.00) 660 (0.26) Age at menarche ≤ 10 years 60,622 (3.9) 3,658 (8.7) 16 (0.25) 18 (0.36) 1,800 (4.4) - 3 (0.09) 1,760 (5.8) 278 (0.09) 26,924 (4.2) 14,720 (6.8) 11,445 (4.5) 11–12 years 457,022 (29.6) 18,046 (42.8) 759 (11.9) 635 (12.5) 14,635 (35.4) - 282 (8.47) 10,787 (35.8) 16,130 (5.4) 220,840 (34.6) 90,177 (41.8) 84,731 (33.2) 13–14 years 624,908 (40.4) 15,807 (37.5) 3,931 (61.7) 2,817 (55.6) 18,925 (45.8) - 1482 (44.5) 13,111 (43.5) 84,506 (28.1) 285,866 (44.7) 89,002 (41.2) 109,461 (42.8) ≥ 15 years 375,784 (24.3) 4,365 (10.3) 1,664 (26.1) 1,570 (31.0) 5,399 (13.1) - 1536 (46.1) 3,877 (12.9) 199,947 (66.4) 95,559 (15.0) 19,860 (9.2) 42,007 (16.4) Unknown 27,881 (1.8) 318 (0.75) 2 (0.03) 25 (0.49) 576 (1.4) 6,480 (100) 26 (0.8) 613 (2.0) 48 (0.02) 9,837 (1.5) 2,146 (0.99) 7,810 (3.1) Parity None 187,425 (12.1) 6,542 (15.5) 329 (5.2) 295 (5.8) 15,748 (38.1) 3,244 (50.1) 255 (7.66) 3,739 (12.4) 3,956 (1.3) 72,831 (11.4) 32,816 (15.2) 47,670 (18.7) One 254,901 (16.5) 5,457 (12.9) 546 (8.6) 385 (7.6) 5,357 (13.0) 917 (14.2) 184 (5.53) 3,748 (12.4) 103,690 (34.5) 78,095 (12.2) 22,460 (10.4) 34,062 (13.3) Two 593,107 (38.4) 13,342 (31.6) 1,692 (26.6) 1,287 (25.4) 12,261 (29.7) 1,386 (21.4) 1148 (34.5) 11,668 (38.7) 95,596 (31.8) 287,141 (44.9) 55,974 (25.9) 111,612 (43.7) 3–4 430,594 (27.8) 13,045 (30.9) 2,489 (39.1) 1,983 (39.2) 7,062 (17.1) 714 (11.0) 1550 (46.6) 7,255 (24.1) 77,933 (25.9) 182,369 (28.5) 78,618 (36.4) 57,576 (22.5) 5–9 70,558 (4.6) 3,066 (7.3) 1,211 (19.0) 1,042 (20.6) 526 (1.3) 63 (0.97) 173 (5.20) 603 (2.0) 19,542 (6.5) 17,126 (2.7) 23,014 (10.7) 4,192 (1.6) ≥ 10 1,305 (0.08) 133 (0.32) 59 (0.93) 52 (1.0) 2 (0.00) 1 (0.02) 0 (0.00) 12 (0.04) 192 (0.06) 63 (0.01) 746 (0.35) 45 (0.02) Unknown 8,327 (0.54) 609 (1.4) 46 (0.72) 21 (0.41) 379 (0.92) 155 (2.4) 19 (0.6) 3,123 (10.4) 0 (0.00) 1,401 (0.22) 2,277 (1.1) 297 (0.12) Age at first birth ≤ 19 years 157,185 (10.2) 5,947 (14.1) - - 1,489 (3.6) 195 (3.0) - 1,661 (5.5) 28,021 (9.3) 62,803 (9.8) 37,301 (17.3) 19,768 (7.7) 20–24 years 619,652 (40.1) 13,002 (30.8) - - 7,934 (19.2) 967 (14.9) - 8,101 (26.9) 170,982 (56.8) 258,825 (40.5) 92,737 (43.0) 67,104 (26.3) 25–29 years 401,728 (26.0) 8,627 (20.4) - - 9,889 (23.9) 1,259 (19.4) - 8,883 (29.5) 86,929 (28.9) 173,713 (27.2) 38,202 (17.7) 74,226 (29.1) 30–34 years 108,882 (7.0) 3,479 (8.2) - - 4,444 (10.8) 490 (7.6) - 3,434 (11.4) 9,222 (3.1) 45,920 (7.2) 9,717 (4.5) 32,176 (12.6) 35–39 years 30,023 (1.9) 1,049 (2.5) - - 1,248 (3.0) 134 (2.1) - 1,025 (3.4) 1,433 (0.48) 11,223 (1.8) 2,387 (1.1) 11,524 (4.5) ≥ 40 years 5,511 (0.36) 236 (0.56) - - 193 (0.47) 23 (0.35) - 157 (0.52) 218 (0.07) 2,002 (0.31) 413 (0.19) 2,269 (0.89) No children 187,425 (12.1) 6,542 (15.5) 329 (5.2) 295 (5.8) 15,748 (38.1) 3,244 (50.1) 255 (7.7) 3,739 (12.4) 3,956 (1.3) 72,831 (11.4) 32,816 (15.2) 47,670 (18.7) Unknown 35,811 (2.3) 3,312 (7.8) 6,043 (94.8) 4,770 (94.2) 390 (0.94) 168 (2.6) 3074 (92.3) 3,148 (10.4) 148 (0.05) 11,709 (1.8) 2,332 (1.1) 717 (0.28) Menopausal status Pre-menopausal 244,562 (15.8) 9,689 (23.0) 4,018 (63.1) 2,941 (58.1) 24,718 (59.8) 4,754 (73.4) 1232 (37.0) 11,796 (39.1) 128,741 (42.8) 1 (0.00) 0 (0.00) 56,672 (22.2) Post-menopausal 1,301,655 (84.2) 32,505 (77.0) 2,354 (36.9) 2,124 (41.9) 16,617 (40.2) 1,726 (26.6) 2097 (63.0) 18,352 (60.9) 172,168 (57.2) 639,025 (100.0) 215,905 (100) 198,782 (77.8) Age at menopause (postmenopausal women only) < 40 years 77,087 (5.9) 2,594 (8.0) 406 (17.2) 292 (13.7) 0 (0.00) - 131 (6.2) 2,004 (10.9) 6,464 (3.8) 21,158 (3.3) 38,407 (17.8) 5,631 (2.8) 40–44 years 124,498 (9.6) 3,005 (9.2) 639 (27.1) 518 (24.4) 1,508 (9.1) - 251 (12.0) 2,008 (10.9) 18,184 (10.6) 52,184 (8.2) 33,393 (15.5) 12,808 (6.4) 45–49 years 296,861 (22.8) 5,383 (16.6) 757 (32.2) 653 (30.7) 3,142 (18.9) - 556 (26.5) 3,953 (21.5) 65,017 (37.8) 132,074 (20.7) 51,357 (23.8) 33,969 (17.1) 50–54 years 438,854 (33.7) 7,762 (23.9) 340 (14.4) 375 (17.7) 4,893 (29.4) - 964 (46.0) 6,294 (34.3) 60,141 (34.9) 223,470 (35.0) 66,050 (30.6) 68,565 (34.5) ≥ 55 years 104,681 (8.0) 12,232 (37.6) 103 (4.4) 73 (3.4) 739 (4.4) - 173 (8.2) 1,051 (5.7) 7,779 (4.5) 46,200 (7.2) 14,617 (6.8) 21,714 (10.9) Unknown 259,674 (19.9) 1,529 (4.7) 109 (4.6) 213 (10.0) 6,335 (38.1) 1,726 (100) 22 (1.0) 3,042 (16.6) 14,583 (8.5) 163,939 (25.7) 12,081 (5.6) 56,095 (28.2) Ever used oral contraceptives Yes 791,983 (51.3) 24,802 (58.8) 223 (3.5) 349 (6.9) 30,475 (73.7) 3,582 (55.3) 523 (15.7) 20,167 (66.9) 29,611 (9.8) 391,488 (61.3) 84,234 (39.0) 207,052 (81.1) No 742,243 (48.1) 17,392 (41.2) 6,148 (96.5) 4,688 (92.6) 10,503 (25.4) 2,848 (44.0) 2778 (83.4) 9,521 (31.6) 271,252 (90.1) 243,805 (38.2) 128,537 (59.5) 47,549 (18.6) Unknown 8,662 (0.6) - 1 (0.02) 28 (0.55) 357 (0.86) 50 (0.77) 28 (0.01) 460 (1.5) 46 (0.02) 3,733 (0.58) 3,134 (1.45) 853 (0.33) Ever used hormone replacement therapy Yes 584,677 (37.8) 16,619 (39.4) - - 7,506 (18.2) - 654 (19.6) 8,198 (27.2) - 341,137 (53.4) 114,186 (52.9) 96,377 (37.7) No 628,851 (40.7) 24,294 (57.6) - - 33,239 (80.4) - 1432 (43.0) 20,997 (69.6) - 289,096 (45.2) 101,719 (47.1) 158,074 (61.9) Unknown 332,689 (21.5) 1,281 (3.0) 6,372 (100) 5,065 (100) 590 (1.4) 6,480 (100) 1243 (37.3) 953 (3.2) 300,909 (100) 8,793 (1.4) 0 (0.00) 1,003 (0.39) Abbreviations: AHS-2, Adventist Health Study-2; CARRS, Centre for cArdiometabolic Risk Reduction in South Asia; CKB, China Kadoorie Biobank; EPIC, European Prospective Investigation into Cancer and Nutrition; MWS, Million Women Study; NIH-AARP, National Institutes of Health-AARP Diet and Health Study; OVS, Oxford Vegetarian Study; TCHS, Tzu Chi Health Study; UKWCS, UK Women’s Cohort Study. 1All values are N (%). 2Sex-specific tertiles of metabolic equivalents. c indicates that no information was available for this variable in the specified cohort. The original article [1] has been corrected

Underuse of medication for circulatory disorders among unmarried women and men in Norway?

BACKGROUND: It is well established that unmarried people have higher mortality from circulatory diseases and higher all-cause mortality than the married, and these marital status differences seem to be increasing. However, much remains to be known about the underlying mechanisms. Our objective was to examine marital status differences in the purchase of medication for circulatory diseases, and risk factors for them, which may indicate underuse of such medication by some marital status groups. METHODS: Using data from registers covering the entire Norwegian population, we analysed marital status differences in the purchase of medicine for eight circulatory disorders by people aged 50-79 in 2004-2008. These differences were compared with those in circulatory disease mortality during 2004-2007, considered as indicating probable differences in disease burden. RESULTS: The unmarried had 1.4-2.8 times higher mortality from the four types of circulatory diseases considered. However, the never-married in particular purchased less medicine for these diseases, or precursor risk factors of these diseases, primarily because of a low chance of making a first purchase. The picture was more mixed for the divorced and widowed. Both groups purchased less of some of these medicines than the married, but, especially in the case of the widowed, relatively more of other types of medicine. In contrast to the never-married, divorced and widowed people were as least as likely as the married to make a first purchase, but adherence rates thereafter, indicated by continuing purchases, were lower. CONCLUSION: The most plausible interpretation of the findings is that compared with married people, especially the never-married more often have circulatory disorders that are undiagnosed or for which they for other reasons underuse medication. Inadequate use of these potentially very efficient medicines in such a large population group is a serious public health challenge which needs further investigation. It is possible that marital status differences in use of medicines for circulatory disorders combined with an increasing importance of these medicines have contributed to the widening marital status gap in mortality observed in several countries. This also requires further investigation