Socioeconomic predictors of referral to a diagnostic centre on suspected adverse events following HPV vaccination

Socioeconomic predictors of referral to a diagnostic centre on suspected adverse events following... Abstract Background In Denmark, the human papillomavirus (HPV) vaccines have been suspected of adverse events since 2014. However, as no causal associations between the HPV vaccines and numerous diseases have been demonstrated, factors prior to vaccination may influence the risk of suspecting the HPV vaccines of causing symptoms. We studied the associations between individual and parental socioeconomic characteristics and the risk of referral to a diagnostic centre in a female population aged 11–29 years with a first HPV vaccination in January 2008 to June 2015. Methods Individual and parental data from national registries were linked using the unique personal identification number. Logistic regression analyses were used to estimate crude and adjusted odds ratio’s according to each individual and parental socioeconomic factor with two-sided 95% 95% CI. Results The cohort consisted of 453 216 individuals of which 1316 (0.29%) were referred to a diagnostic centre in 2015. Having a mother outside the workforce or an unemployed mother was associated with an increased risk of referral, while girls and women who had fathers with a higher educational level were less likely to be referred. In addition, women aged 20–29 years who were unemployed or outside the workforce prior to vaccination had increased odds of being referred to a diagnostic centre. Conclusion We found social inequality in the referral to a diagnostic centre following HPV vaccination. This might be explained by an increased morbidity in girls and women of lower socioeconomic status. Introduction The human papillomavirus (HPV) vaccine was approved in 2006, and in 2009 the quadrivalent HPV vaccine was implemented in the Danish childhood vaccination programme with a primary target group of 12-year-old girls. In addition, catch-up programmes have been offered to increase coverage rates. To date, more than 600 000 individuals have been vaccinated against HPV, primarily with the quadrivalent vaccine. Pre- and post-licensure efficacy studies have demonstrated high protection against HPV infection and dysplasia,1–3 while safety studies show no increased risk of chronic fatigue syndrome, autoimmune, neurological or venous thromboembolic adverse events following HPV vaccination in adolescent girls or adult women.4–7 However, by 2016, more than 2300 adverse events have been reported to the Danish Medicines Agency as suspected adverse events to the HPV vaccines.8 Of these, 1023 were considered serious adverse events resulting in hospitalisation, missing school or work or death.8 Common symptoms reported were headache, fatigue, dizziness, syncope and nausea, whereas other reports included diagnoses such as postural orthostatic tachycardia syndrome and complex regional pain syndrome.9 As a response to the public debate about the serious adverse events following HPV vaccination, a diagnostic centre in each Danish region was tasked to further examine girls and women presenting with unexplained symptoms with a temporal association to HPV vaccination. Referral to the centres began in 2015 and the main task at the centres is to examine the referred females through a bio-psycho-social perspective to recommend further treatment and rehabilitation. Despite several studies showing no causal link between the vaccines and various diseases, the debate about the vaccines’ safety is ongoing. Studies have shown that women reporting symptoms to the Danish Medicines Agency and women referred to the diagnostic centres had a different health care seeking behaviour and use of psychiatric medicines prior to vaccination compared with other HPV-vaccinated women.10,11 Hence, factors prior to vaccination may be important for suspecting the HPV vaccines of causing the reported symptoms. So far, little attention has been paid to the sociodemographic background of the referred girls and young women and whether this background is associated with the risk of being referred. Therefore, the aim of this study was to examine the association between individual and parental demographic and socioeconomic characteristics and referral to a diagnostic centre due to suspected adverse events following HPV vaccination. Methods The study was conducted as a registry-based cohort study. People living in Denmark have a unique personal identification number (PIN), enabling linkage between national health and demographic databases. Using the PINs as identifiers, we identified all girls and women aged 11- to 29-years old residing in Denmark and having a first HPV vaccine injection (Gardasil or Cervarix) in the period January 2008 to June 2015. Girls and women vaccinated in the childhood vaccination programme or in the catch-up programmes were identified in the National Health Insurance Register with a service code registration (service codes 8328, 8329, 8330, 8334, 8335 or 8336), while women who redeemed a prescription for the vaccines were identified in the Register of Medicinal Product Statistics (Anatomic Therapeutic Chemical code J07BM). The PINs enabled linkage to the parents and the cohort was linked to Statistics Denmark’s population-based databases, containing information on residence and individual and parental socioeconomic factors.12 Girls and women who had missing information on residence, individual or parental socioeconomic factors were excluded from the study cohort. Participant informed consent was not required. The Danish Data Protection Agency (journal number 2015-57-0002) and the Danish Patient Safety Authority approved the study. Study variables The outcome of interest was referral to a diagnostic centre between January–December 2015 because of suspected adverse events following HPV vaccination. PINs of referred women were obtained from each diagnostic centre and linked to the study population to confirm vaccination. The exposures of interest were parental level of education and occupational status. Information on each socioeconomic factor was obtained the year prior to vaccination and when information on educational level or occupational status was missing, data was instead obtained two years prior to vaccination. Parental level of education was split into five groups based on DISCED-1513; Early childhood education, primary education or lower secondary education (DISCED levels 05, 10 and 20), upper secondary education (DISCED level 30), short cycle tertiary education (DISCED level 50), short cycle tertiary education, bachelor or equivalent (DISCED level 60), and master’s or equivalent, or third-cycle programmes doctoral, PhD programmes or equivalent (DISCED levels 70 and 80). Occupational status of each parent was divided into three groups; employed, self-employed or student, unemployed (e.g. receiving unemployment benefit, sickness benefit, social assistance or education allowance), or outside the workforce (e.g. old-age pension, early retirement pension and disability pension). Furthermore, educational level (primary or lower secondary education, upper secondary or high school or higher education) and occupational status (employed, student or outside the workforce including unemployed women) for the vaccinated females aged 20–29 years were studied. Covariates included year of vaccination (2008–09, 2010–11, 2012–13 or 2014–15), age at vaccination (continuously) and place of residence at the time of vaccination. Statistical analyses Characteristics for the study population on exposures and covariates were summarized using numbers and percentages. The association between socioeconomic characteristics and risk of referral to a diagnostic centre was estimated in a logistic model. First, crude associations of each parental socioeconomic characteristic were estimated (model 1), followed by a model adjusted for covariates (model 2). Finally, in model 3, each exposure was mutually adjusted for the other potential socioeconomic confounders. Odds ratios (OR) and the corresponding 95% CI were determined. Potential modification by age was assessed by including interaction between age and each parental socioeconomic factor. As no interaction between age and the socioeconomic factors was found [P-values ranging 0.13–0.96 (model 2)], the results are not presented further. A subanalysis of the women aged 20–29 years was performed, evaluating the associations between the vaccinated women’s own socioeconomic characteristics and the risk of referral to a diagnostic centre. Results During the study period, we identified 527 939 records of a first HPV vaccination in females aged 11–29. After individuals with missing information on sociodemographic variables were excluded, the study cohort consisted of the remaining 453 216 individuals (figure 1). By the end of 2015, 1420 of the included females had been referred to a diagnostic centre on suspected adverse events of the vaccine. Among the women who were referred, 104 individuals were excluded because they did not have a registered vaccination according to our data. The remaining 1316 referred women comprised 0.29% of study cohort and the proportion of referred women were 0.30, 0.36, 0.26 and 0.25% of women vaccinated in 2008–09, 2010–11, 2012–13 and 2014–15, respectively. Figure 1 View largeDownload slide Flow chart for study participants a: The numbers are not mutually exclusive Figure 1 View largeDownload slide Flow chart for study participants a: The numbers are not mutually exclusive Characteristics of the vaccinated girls and women are presented in table 1. The majority of women had a working parent or a parent whose highest completed education was primary or secondary school or vocational training. In addition, the majority of women were vaccinated in 2008–09 and 2012–13 at the age of 11–19 years and resided primarily in the Capital region. This corresponds to the age group covered under the childhood vaccination programme and the years and age groups in which the catch-up programmes were in place. Table 2 shows the results of the multivariate logistic regression analyses of the associations between parental socioeconomic status (SES) and the risk of referral to a diagnostic centre. All three models showed a social gradient in risk of referral according to one or more of the socioeconomic variables. Thus, the odds of referral to a diagnostic centre was lower among girls in highly educated or employed families compared to girls in families of lower SES. When adjusting for the other socioeconomic factors and covariates, most associations were attenuated. Girls and women who had a mother with a master’s degree or a father with a bachelor’s or master’s degree were less likely to be referred to a diagnostic centre (OR= 0.73; 95% CI 0.53–1.00, OR = 0.76; 95% CI 0.61–0.95 and OR = 0.72; 95% CI 0.55–0.94, respectively). Girls and women who had unemployed mothers or mothers outside the workforce were more likely to be referred to a diagnostic centre (OR = 1.21; 95% CI 1.02–1.43 and OR = 1.59; 95% CI 1.28–1.96, respectively). Table 1 Demographic characteristics of girls aged 11–29 years vaccinated with ≥1 HPV injection in the period January 2008 to June 2015, n = 453 216   n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08    n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08  a For vaccinated women aged 20–29 years, n = 145 714. Table 1 Demographic characteristics of girls aged 11–29 years vaccinated with ≥1 HPV injection in the period January 2008 to June 2015, n = 453 216   n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08    n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08  a For vaccinated women aged 20–29 years, n = 145 714. Table 2 The associations between parental socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among girls aged 11–29 years in Denmark, n = 453 216   Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)    Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio; CI, confidence interval. a Adjusted for age, year of vaccination and residence using a logistic regression model. b Adjusted for age, year of vaccination, residence and parental socioeconomic factors using a logistic regression model. Table 2 The associations between parental socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among girls aged 11–29 years in Denmark, n = 453 216   Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)    Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio; CI, confidence interval. a Adjusted for age, year of vaccination and residence using a logistic regression model. b Adjusted for age, year of vaccination, residence and parental socioeconomic factors using a logistic regression model. Additionally, women aged 20–29 years were slightly less likely to be referred compared to girls aged 11–19 (OR = 0.96; 95% CI 0.95–0.97) (Data not shown). A significant difference in risk of referral in relation to place of residence was also observed. Girls living in Central Denmark Region (OR = 0.74; 95% CI 0.63–0.87) had a lower risk of referral compared to girls living in the Capital, while girls and women living in Zealand were more likely to be referred (OR = 1.37; 95% CI 1.17–1.61). No statistically significant associations between residence in North Denmark or Southern Denmark compared with the Capital region was observed (OR = 1.10; 95% CI 0.91–1.33 and OR = 0.87; 95% CI 0.74–1.02, respectively) (Data not shown). In table 3, the results of the subgroup analyses including only women between 20 and 29 years at the time of vaccination are presented. Among women who had finished secondary school or higher-level education, we found a lower risk of referral compared with women whose highest completed education was primary school, although the association was not statistically significant. An increased risk of referral was also seen among women who were outside the workforce or unemployed at the time of vaccination (OR = 1.93; 95% CI 1.39–2.68). The association persisted after adjustment for covariates and parental SES. Table 3 The associations between socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among women aged 20–29 years in Denmark, n = 145 714   Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)    Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio. CI, confidence interval. a Adjusted for year of vaccination, residence and age using a logistic regression model. b Adjusted for year of vaccination, residence, age and parental socioeconomic factors using a logistic regression model. Table 3 The associations between socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among women aged 20–29 years in Denmark, n = 145 714   Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)    Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio. CI, confidence interval. a Adjusted for year of vaccination, residence and age using a logistic regression model. b Adjusted for year of vaccination, residence, age and parental socioeconomic factors using a logistic regression model. Discussion The study found that only 0.29% of girls and women aged 11–29 years who had a first HPV vaccination from January 2008 to June 2015 were referred to a diagnostic centre during 2015. Referral was more likely in girls and women who had a parent with lower levels of education, an unemployed mother or a mother outside the workforce. In addition, among women aged 20–29 years, an inverse gradient in the risk of referral was observed according to educational level, although the associations were not statistically significant. This study adds to the limited knowledge about the women reporting adverse events following HPV vaccination. Danish females referred to a diagnostic centre or reporting severe adverse events following HPV vaccination are shown to have had a higher pre-vaccination use of psychiatric medicine and more contact to health care compared with other HPV vaccination females.10,11 Combined, the results of these studies suggest that factors prior to vaccination are associated with the risk of reporting suspected adverse events. Since March 2016 when we received data on referrals, the number of referred girls and women has increased. The latest official update on the number of referred women show that as of 1 March 2017, 2129 girls and women have been referred to a diagnostic centre.14 At present, we do not know if the referred females included in this study are representative of all referred cases. Referral rates to the diagnostics centres have declined in 2016 and 2017, possibly because of fewer vaccinated girls.14 Also the distribution of the investigated exposures may have changed. Possible explanations for the findings The results show that low levels of parental education and maternal unemployment as well as unemployment in women aged 20–29 years were significantly associated with an increased risk of being referred to a diagnostic centre. These associations can potentially be partly explained by an easier access to specialist health care among girls and women from socioeconomic advantaged families.15 The risk of referral and thus the risk of experiencing possible adverse events following vaccination may also be caused by an underlying difference in the risk of morbidity between girls of low SES and girls of high SES. As in the adult population, adolescents of low SES are disproportionally affected by diseases and engaged in negative health behaviours.16–18 The results by Lützen et al.11 and Mølbak et al.10 showing higher use of some health care services prior to vaccination in females referred to a diagnostic centre and in females reporting symptoms to the Danish Medicines Agency may suggest an increased morbidity prior to vaccination in the referred women. Methodological considerations A strength of the study is the prospective study design and the use of nationwide registers, which eliminates the risk of recall bias. Furthermore, the data obtained from the registers were considered to be of high quality.19–22 A total of 527 939 women met the inclusion criteria, of which 74 723 were excluded due to missing sociodemographic information. The excluded individuals comprised 14% of the total study population and were primarily aged 20–29 years, lived in the Capital region and were vaccinated in 2012/13. Missing information occurred primarily because linkage to the parents was not obtained. Our study also has some limitations. General practitioners are reimbursed by registering their activities at the National Health Services, leaving severe underreporting of girls covered under the childhood vaccination programme or one of the catch-up programmes unlikely. Missing information on vaccinations given to older girls is more likely, as women vaccinated in other settings, such as fitness centres and drugstores, were not included in the study cohort. Given that the vaccine was free of charge, the missing information is not expected to cause selection bias. Among the 1420 referred to a diagnostic centre in 2015, 104 referred women were excluded due to missing registration on vaccination. Register errors are likely the reason for missing vaccination registration and since this is rare and unrelated to both exposures and later referral, this missing registration is not considered to have caused selection bias. Mortality rates are low in the studied age groups,23 but 3–5% of 20- to 29-year olds yearly move to another country.23 As relocation may be more likely in women not experiencing adverse events and who have the financial resources to complete such a move, the effect of occupational status of the vaccinated women on the risk of referral could be underestimated. Additionally, we used highest complete education at vaccination as an indicator of SES of the vaccinated women; however, because this measure is correlated with age, some women may have completed additional degrees the years following vaccination. Adjustment for age did, however, not change the associations between educational level and risk of referral. In conclusion, in this nationwide population-based cohort study, we found that being referred to a diagnostic centre due to suspected adverse events following HPV vaccination was associated with having a mother who was unemployed or outside the workforce and low levels of parental education prior to vaccination. Moreover, referrals were associated with unemployment among young adult women the year prior to vaccination. These associations may partly be caused by an increased morbidity prior to vaccination in females of low SES. However, other studies are needed to explain the causal mechanisms between individual and parental SES and risk of referral. Conflicts of interest: None declared. Key points Referral to a diagnostic centre due to suspected adverse events following HPV vaccination was rare (only 0.29%). We found that referral was more likely in girls of parents with low levels of education, in girls of mothers outside the workforce and in girls with unemployed mothers. The associations between socioeconomic factor and risk of referral may partly be caused by increased morbidity prior to vaccination in females of low socioeconomic status. References 1 Schiller JT, Castellsagué X, Garland SM. A review of clinical trials of human papillomavirus prophylactic vaccines. Vaccine  2012; 30: F123– 38. Google Scholar CrossRef Search ADS PubMed  2 Vichnin M, Bonanni P, Klein NP, et al.   An overview of quadrivalent human papillomavirus vaccine safety: 2006 to 2015. Pediatr Infect Dis J  2015; 34: 983– 91. Google Scholar CrossRef Search ADS PubMed  3 Baldur-Felskov B, Dehlendorff C, Munk C, Kjaer SK. Early impact of human papillomavirus vaccination on cervical neoplasia - Nationwide follow-up of young danish women. J Natl Cancer Inst  2014; 106: djt460. Google Scholar CrossRef Search ADS PubMed  4 Arnheim-Dahlstrom L, Pasternak B, Svanstrom H, et al.   Autoimmune, neurological, and venous thromboembolic adverse events after immunisation of adolescent girls with quadrivalent human papillomavirus vaccine in Denmark and Sweden: cohort study. Bmj  2013; 347: f5906. Google Scholar CrossRef Search ADS PubMed  5 Madrid Scheller N, Svanström H, Pasternak B, et al.   Quadrivalent HPV vaccination and risk of multiple sclerosis and other demyelinating diseases of the central nervous system. Jama  2015; 313: 54– 61. Google Scholar CrossRef Search ADS PubMed  6 Feiring B, Laake I, Bakken IJ, et al.   HPV vaccination and risk of chronic fatigue syndrome/myalgic encephalomyelitis: a nationwide register-based study from Norway. Vaccine  2017; 35: 4203– 12. Google Scholar CrossRef Search ADS PubMed  7 Hviid A, Svanström H, Scheller NM, Grönlund O, Pasternak B, Arnheim-Dahlström L. Human papillomavirus vaccination of adult women and risk of autoimmune and neurological diseases. J Intern Med  2017; 1– 12. 8 Danish Health Authority and Danish Medicines Agency, Denmark. HPV-vaccination beskytter mod livmoderhalskræft (HPV vaccination protects against cervical cancer). Copenhagen: Danish Health Authority and Danish Medicines Agency, 2016. 9 Lægemiddelstyrelsen. Drug Analysis Print. Human Papilloma Virus . Copenhagen: Lægemiddelstyrelsen, 2016. 10 Mølbak K, Hansen ND, Valentiner-Branth P. Pre-vaccination care-seeking in females reporting severe adverse reactions to hpv vaccine. a registry based case-control study. Hozbor DF, editor. PLoS One  2016; 11: e0162520. Google Scholar CrossRef Search ADS PubMed  11 Lützen TH, Bech BH, Mehlsen J, et al.   Psychiatric conditions and general practitioner attendance prior to HPV vaccination and the risk of referral to a specialized hospital setting because of suspected adverse events following HPV vaccination: a register-based, matched case – control study. Clin Epidemiol  2017; 9: 465– 73. Google Scholar CrossRef Search ADS PubMed  12 Statistics Denmark[Internet]. [cited 2017 Sep 25]. Available at: http://www.dst.dk/en 13 Statistics Denmark. Classification of Educational Levels . 2017. Available at: http://www.dst.dk/extranet/uddannelsesklassifikation/Niveau_Level.html ( 25 September 2017, date last accessed). 14 Danske Regions. Status over aktiviteten på regionernes Én indgang-afdelinger pr. 1. marts 2017 (Update on the activities at the regional diagnostic centre per 1 March 2017). Copenhagen: Danish Regions, 2017. 15 Sørensen TH, Olsen KR, Vedsted P. Association between general practice referral rates and patients’ socioeconomic status and access to specialised health care. A population-based nationwide study. Health Policy (New York)  2009; 92: 180– 6. Google Scholar CrossRef Search ADS   16 Chen E, Matthews KA, Boyce WT. Socioeconomic differences in children’s health: how and why do these relationships change with age? Psychol Bull  2002; 128: 295– 329. Google Scholar CrossRef Search ADS PubMed  17 Pedersen CR, Madsen M. Parents’ labour market participation as a predictor of children’s health and wellbeing: a comparative study in five Nordic countries. J Epidemiol Community Heal  2002; 56: 861– 7. Google Scholar CrossRef Search ADS   18 Sleskova M, Salonna F, Geckova AM, et al.   Unemployment and the health of Slovak adolescents. J Adolesc Health  2006; 38: 527– 35. Google Scholar CrossRef Search ADS PubMed  19 Jensen VM, Rasmussen AW. The Danish Education Registers. Scand J Public Health  2011; 39: 91– 4. Google Scholar CrossRef Search ADS PubMed  20 Petersson F, Baadsgaard M, Thygesen LC. Danish registers on personal labour market affiliation. Scand J Public Health  2011; 39: 95– 8. Google Scholar CrossRef Search ADS PubMed  21 Lynge E, Sandegaard JL, Rebolj M. The Danish national patient register. Scand J Public Health  2011; 39: 30– 3. Google Scholar CrossRef Search ADS PubMed  22 Andersen JS, Olivarius NDF, Krasnik A. The Danish national health service register. Scand J Public Health  2011; 39: 34– 7. Google Scholar CrossRef Search ADS PubMed  23 Statistics Denmark. Vital Statistics 2016 , Copenhagen: Statistics Denmark, 2017; 1– 116. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

Socioeconomic predictors of referral to a diagnostic centre on suspected adverse events following HPV vaccination

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
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1101-1262
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1464-360X
D.O.I.
10.1093/eurpub/cky088
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Abstract

Abstract Background In Denmark, the human papillomavirus (HPV) vaccines have been suspected of adverse events since 2014. However, as no causal associations between the HPV vaccines and numerous diseases have been demonstrated, factors prior to vaccination may influence the risk of suspecting the HPV vaccines of causing symptoms. We studied the associations between individual and parental socioeconomic characteristics and the risk of referral to a diagnostic centre in a female population aged 11–29 years with a first HPV vaccination in January 2008 to June 2015. Methods Individual and parental data from national registries were linked using the unique personal identification number. Logistic regression analyses were used to estimate crude and adjusted odds ratio’s according to each individual and parental socioeconomic factor with two-sided 95% 95% CI. Results The cohort consisted of 453 216 individuals of which 1316 (0.29%) were referred to a diagnostic centre in 2015. Having a mother outside the workforce or an unemployed mother was associated with an increased risk of referral, while girls and women who had fathers with a higher educational level were less likely to be referred. In addition, women aged 20–29 years who were unemployed or outside the workforce prior to vaccination had increased odds of being referred to a diagnostic centre. Conclusion We found social inequality in the referral to a diagnostic centre following HPV vaccination. This might be explained by an increased morbidity in girls and women of lower socioeconomic status. Introduction The human papillomavirus (HPV) vaccine was approved in 2006, and in 2009 the quadrivalent HPV vaccine was implemented in the Danish childhood vaccination programme with a primary target group of 12-year-old girls. In addition, catch-up programmes have been offered to increase coverage rates. To date, more than 600 000 individuals have been vaccinated against HPV, primarily with the quadrivalent vaccine. Pre- and post-licensure efficacy studies have demonstrated high protection against HPV infection and dysplasia,1–3 while safety studies show no increased risk of chronic fatigue syndrome, autoimmune, neurological or venous thromboembolic adverse events following HPV vaccination in adolescent girls or adult women.4–7 However, by 2016, more than 2300 adverse events have been reported to the Danish Medicines Agency as suspected adverse events to the HPV vaccines.8 Of these, 1023 were considered serious adverse events resulting in hospitalisation, missing school or work or death.8 Common symptoms reported were headache, fatigue, dizziness, syncope and nausea, whereas other reports included diagnoses such as postural orthostatic tachycardia syndrome and complex regional pain syndrome.9 As a response to the public debate about the serious adverse events following HPV vaccination, a diagnostic centre in each Danish region was tasked to further examine girls and women presenting with unexplained symptoms with a temporal association to HPV vaccination. Referral to the centres began in 2015 and the main task at the centres is to examine the referred females through a bio-psycho-social perspective to recommend further treatment and rehabilitation. Despite several studies showing no causal link between the vaccines and various diseases, the debate about the vaccines’ safety is ongoing. Studies have shown that women reporting symptoms to the Danish Medicines Agency and women referred to the diagnostic centres had a different health care seeking behaviour and use of psychiatric medicines prior to vaccination compared with other HPV-vaccinated women.10,11 Hence, factors prior to vaccination may be important for suspecting the HPV vaccines of causing the reported symptoms. So far, little attention has been paid to the sociodemographic background of the referred girls and young women and whether this background is associated with the risk of being referred. Therefore, the aim of this study was to examine the association between individual and parental demographic and socioeconomic characteristics and referral to a diagnostic centre due to suspected adverse events following HPV vaccination. Methods The study was conducted as a registry-based cohort study. People living in Denmark have a unique personal identification number (PIN), enabling linkage between national health and demographic databases. Using the PINs as identifiers, we identified all girls and women aged 11- to 29-years old residing in Denmark and having a first HPV vaccine injection (Gardasil or Cervarix) in the period January 2008 to June 2015. Girls and women vaccinated in the childhood vaccination programme or in the catch-up programmes were identified in the National Health Insurance Register with a service code registration (service codes 8328, 8329, 8330, 8334, 8335 or 8336), while women who redeemed a prescription for the vaccines were identified in the Register of Medicinal Product Statistics (Anatomic Therapeutic Chemical code J07BM). The PINs enabled linkage to the parents and the cohort was linked to Statistics Denmark’s population-based databases, containing information on residence and individual and parental socioeconomic factors.12 Girls and women who had missing information on residence, individual or parental socioeconomic factors were excluded from the study cohort. Participant informed consent was not required. The Danish Data Protection Agency (journal number 2015-57-0002) and the Danish Patient Safety Authority approved the study. Study variables The outcome of interest was referral to a diagnostic centre between January–December 2015 because of suspected adverse events following HPV vaccination. PINs of referred women were obtained from each diagnostic centre and linked to the study population to confirm vaccination. The exposures of interest were parental level of education and occupational status. Information on each socioeconomic factor was obtained the year prior to vaccination and when information on educational level or occupational status was missing, data was instead obtained two years prior to vaccination. Parental level of education was split into five groups based on DISCED-1513; Early childhood education, primary education or lower secondary education (DISCED levels 05, 10 and 20), upper secondary education (DISCED level 30), short cycle tertiary education (DISCED level 50), short cycle tertiary education, bachelor or equivalent (DISCED level 60), and master’s or equivalent, or third-cycle programmes doctoral, PhD programmes or equivalent (DISCED levels 70 and 80). Occupational status of each parent was divided into three groups; employed, self-employed or student, unemployed (e.g. receiving unemployment benefit, sickness benefit, social assistance or education allowance), or outside the workforce (e.g. old-age pension, early retirement pension and disability pension). Furthermore, educational level (primary or lower secondary education, upper secondary or high school or higher education) and occupational status (employed, student or outside the workforce including unemployed women) for the vaccinated females aged 20–29 years were studied. Covariates included year of vaccination (2008–09, 2010–11, 2012–13 or 2014–15), age at vaccination (continuously) and place of residence at the time of vaccination. Statistical analyses Characteristics for the study population on exposures and covariates were summarized using numbers and percentages. The association between socioeconomic characteristics and risk of referral to a diagnostic centre was estimated in a logistic model. First, crude associations of each parental socioeconomic characteristic were estimated (model 1), followed by a model adjusted for covariates (model 2). Finally, in model 3, each exposure was mutually adjusted for the other potential socioeconomic confounders. Odds ratios (OR) and the corresponding 95% CI were determined. Potential modification by age was assessed by including interaction between age and each parental socioeconomic factor. As no interaction between age and the socioeconomic factors was found [P-values ranging 0.13–0.96 (model 2)], the results are not presented further. A subanalysis of the women aged 20–29 years was performed, evaluating the associations between the vaccinated women’s own socioeconomic characteristics and the risk of referral to a diagnostic centre. Results During the study period, we identified 527 939 records of a first HPV vaccination in females aged 11–29. After individuals with missing information on sociodemographic variables were excluded, the study cohort consisted of the remaining 453 216 individuals (figure 1). By the end of 2015, 1420 of the included females had been referred to a diagnostic centre on suspected adverse events of the vaccine. Among the women who were referred, 104 individuals were excluded because they did not have a registered vaccination according to our data. The remaining 1316 referred women comprised 0.29% of study cohort and the proportion of referred women were 0.30, 0.36, 0.26 and 0.25% of women vaccinated in 2008–09, 2010–11, 2012–13 and 2014–15, respectively. Figure 1 View largeDownload slide Flow chart for study participants a: The numbers are not mutually exclusive Figure 1 View largeDownload slide Flow chart for study participants a: The numbers are not mutually exclusive Characteristics of the vaccinated girls and women are presented in table 1. The majority of women had a working parent or a parent whose highest completed education was primary or secondary school or vocational training. In addition, the majority of women were vaccinated in 2008–09 and 2012–13 at the age of 11–19 years and resided primarily in the Capital region. This corresponds to the age group covered under the childhood vaccination programme and the years and age groups in which the catch-up programmes were in place. Table 2 shows the results of the multivariate logistic regression analyses of the associations between parental socioeconomic status (SES) and the risk of referral to a diagnostic centre. All three models showed a social gradient in risk of referral according to one or more of the socioeconomic variables. Thus, the odds of referral to a diagnostic centre was lower among girls in highly educated or employed families compared to girls in families of lower SES. When adjusting for the other socioeconomic factors and covariates, most associations were attenuated. Girls and women who had a mother with a master’s degree or a father with a bachelor’s or master’s degree were less likely to be referred to a diagnostic centre (OR= 0.73; 95% CI 0.53–1.00, OR = 0.76; 95% CI 0.61–0.95 and OR = 0.72; 95% CI 0.55–0.94, respectively). Girls and women who had unemployed mothers or mothers outside the workforce were more likely to be referred to a diagnostic centre (OR = 1.21; 95% CI 1.02–1.43 and OR = 1.59; 95% CI 1.28–1.96, respectively). Table 1 Demographic characteristics of girls aged 11–29 years vaccinated with ≥1 HPV injection in the period January 2008 to June 2015, n = 453 216   n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08    n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08  a For vaccinated women aged 20–29 years, n = 145 714. Table 1 Demographic characteristics of girls aged 11–29 years vaccinated with ≥1 HPV injection in the period January 2008 to June 2015, n = 453 216   n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08    n  %  Mother’s level of education          Primary school  84 843  18.72      Upper secondary or vocational training  198 540  43.81      Short cycle higher education  25 075  5.53      Bachelors or vocational bachelors  112 701  24.87      Masters or PhD programmes  32 057  7.07  Mother’s occupation          Employed, self-employed or student  375 012  82.74      Outside the workforce  28 747  6.34      Unemployed  49 457  10.91  Father’s level of education          Primary school  94 327  20.81      Upper secondary or vocational training  226 933  50.07      Short cycle higher education  25 676  5.67      Bachelors or vocational bachelors  61 552  13.58      Masters or PhD programmes  44 728  9.87  Father’s occupation          Employed, self-employed or student  385 521  85.06      Outside the workforce  29 528  6.52      Unemployed  38 167  8.42  Educational levela          Primary school  37 878  25.99      Upper secondary or vocational training  73 557  41.15      Higher-level education  43 279  32.86  Occupationa          Employed or self-employed  111 202  76.32      Outside the workforce or unemployed  11 974  8.22      Student  22 538  15.47  Age at vaccination          11–19  307 502  67.85      20–29  145 714  32.15  Year of vaccination          2008–09  161 539  35.64      2010–11  73 616  16.24      2012–13  184 151  40.63      2014–15  33 910  7.48  Region of residence          North Denmark  48 755  10.76      Central Denmark  112 799  24.89      Southern Denmark  98 226  21.67      Capital  129 638  28.60      Zealand  63 798  14.08  a For vaccinated women aged 20–29 years, n = 145 714. Table 2 The associations between parental socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among girls aged 11–29 years in Denmark, n = 453 216   Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)    Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio; CI, confidence interval. a Adjusted for age, year of vaccination and residence using a logistic regression model. b Adjusted for age, year of vaccination, residence and parental socioeconomic factors using a logistic regression model. Table 2 The associations between parental socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among girls aged 11–29 years in Denmark, n = 453 216   Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)    Referred (n)  %  OR  ORa  ORb  95% CI  Mother’s level of education                Primary school  252  0.30  1  1  1        Upper secondary or vocational training  640  0.32  1.09  1.04  1.14  (0.97; 1.33)      Short cycle higher education  72  0.29  0.97  0.91  1.03  (0.79; 1.36)      Bachelors or vocational bachelors  296  0.26  0.89  0.86  1.03  (0.86; 1.24)      Masters or PhD programmes  56  0.17  0.59  0.54  0.73  (0.53; 1.00)  Mother’s occupation                  Employed, self-employed or student  1035  0.28  1  1  1        Outside the workforce  108  0.37  1.35  1.58  1.59  (1.28; 1.96)      Unemployed  173  0.35  1.26  1.22  1.21  (1.02; 1.43)  Father’s level of education                  Primary school  291  0.31  1  1  1        Upper secondary or vocational training  721  0.32  1.03  1.02  1.04  (0.91; 1.20)      Short cycle higher education  81  0.32  1.01  0.97  1.01  (0.78; 1.29)      Bachelors or vocational bachelors  136  0.22  0.71  0.71  0.76  (0.61; 0.95)      Masters or PhD programmes  87  0.19  0.63  0.61  0.72  (0.55; 0.94)  Father’s occupation                  Employed, self-employed or student  1123  0.29  1  1  1        Outside the workforce  75  0.25  0.87  1.02  0.90  (0.70; 1.15)      Unemployed  118  0.31  1.07  1.04  0.96  (0.79; 1.16)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio; CI, confidence interval. a Adjusted for age, year of vaccination and residence using a logistic regression model. b Adjusted for age, year of vaccination, residence and parental socioeconomic factors using a logistic regression model. Additionally, women aged 20–29 years were slightly less likely to be referred compared to girls aged 11–19 (OR = 0.96; 95% CI 0.95–0.97) (Data not shown). A significant difference in risk of referral in relation to place of residence was also observed. Girls living in Central Denmark Region (OR = 0.74; 95% CI 0.63–0.87) had a lower risk of referral compared to girls living in the Capital, while girls and women living in Zealand were more likely to be referred (OR = 1.37; 95% CI 1.17–1.61). No statistically significant associations between residence in North Denmark or Southern Denmark compared with the Capital region was observed (OR = 1.10; 95% CI 0.91–1.33 and OR = 0.87; 95% CI 0.74–1.02, respectively) (Data not shown). In table 3, the results of the subgroup analyses including only women between 20 and 29 years at the time of vaccination are presented. Among women who had finished secondary school or higher-level education, we found a lower risk of referral compared with women whose highest completed education was primary school, although the association was not statistically significant. An increased risk of referral was also seen among women who were outside the workforce or unemployed at the time of vaccination (OR = 1.93; 95% CI 1.39–2.68). The association persisted after adjustment for covariates and parental SES. Table 3 The associations between socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among women aged 20–29 years in Denmark, n = 145 714   Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)    Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio. CI, confidence interval. a Adjusted for year of vaccination, residence and age using a logistic regression model. b Adjusted for year of vaccination, residence, age and parental socioeconomic factors using a logistic regression model. Table 3 The associations between socioeconomic factors and risk of referral to a diagnostic centre on suspected adverse events following HPV vaccination among women aged 20–29 years in Denmark, n = 145 714   Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)    Referred (n)  %  OR  ORa  ORb  95% CI  Educational level                  Primary school  117  0.31  1  1  1        Upper secondary or vocational training  130  0.18  0.57  0.60  0.76  (0.57; 1.00)      Higher-level education  53  0.15  0.50  0.54  0.71  (0.49; 1.03)  Occupation                  Employed or self-employed  211  0.19  1  1  1        Outside the workforce or unemployed  53  0.44  2.34  2.34  1.93  (1.39; 2.68)      Student  36  0.16  0.84  0.83  0.87  (0.61; 1.24)  Estimates highlighted in bold have P-values <0.05. OR, odds ratio. CI, confidence interval. a Adjusted for year of vaccination, residence and age using a logistic regression model. b Adjusted for year of vaccination, residence, age and parental socioeconomic factors using a logistic regression model. Discussion The study found that only 0.29% of girls and women aged 11–29 years who had a first HPV vaccination from January 2008 to June 2015 were referred to a diagnostic centre during 2015. Referral was more likely in girls and women who had a parent with lower levels of education, an unemployed mother or a mother outside the workforce. In addition, among women aged 20–29 years, an inverse gradient in the risk of referral was observed according to educational level, although the associations were not statistically significant. This study adds to the limited knowledge about the women reporting adverse events following HPV vaccination. Danish females referred to a diagnostic centre or reporting severe adverse events following HPV vaccination are shown to have had a higher pre-vaccination use of psychiatric medicine and more contact to health care compared with other HPV vaccination females.10,11 Combined, the results of these studies suggest that factors prior to vaccination are associated with the risk of reporting suspected adverse events. Since March 2016 when we received data on referrals, the number of referred girls and women has increased. The latest official update on the number of referred women show that as of 1 March 2017, 2129 girls and women have been referred to a diagnostic centre.14 At present, we do not know if the referred females included in this study are representative of all referred cases. Referral rates to the diagnostics centres have declined in 2016 and 2017, possibly because of fewer vaccinated girls.14 Also the distribution of the investigated exposures may have changed. Possible explanations for the findings The results show that low levels of parental education and maternal unemployment as well as unemployment in women aged 20–29 years were significantly associated with an increased risk of being referred to a diagnostic centre. These associations can potentially be partly explained by an easier access to specialist health care among girls and women from socioeconomic advantaged families.15 The risk of referral and thus the risk of experiencing possible adverse events following vaccination may also be caused by an underlying difference in the risk of morbidity between girls of low SES and girls of high SES. As in the adult population, adolescents of low SES are disproportionally affected by diseases and engaged in negative health behaviours.16–18 The results by Lützen et al.11 and Mølbak et al.10 showing higher use of some health care services prior to vaccination in females referred to a diagnostic centre and in females reporting symptoms to the Danish Medicines Agency may suggest an increased morbidity prior to vaccination in the referred women. Methodological considerations A strength of the study is the prospective study design and the use of nationwide registers, which eliminates the risk of recall bias. Furthermore, the data obtained from the registers were considered to be of high quality.19–22 A total of 527 939 women met the inclusion criteria, of which 74 723 were excluded due to missing sociodemographic information. The excluded individuals comprised 14% of the total study population and were primarily aged 20–29 years, lived in the Capital region and were vaccinated in 2012/13. Missing information occurred primarily because linkage to the parents was not obtained. Our study also has some limitations. General practitioners are reimbursed by registering their activities at the National Health Services, leaving severe underreporting of girls covered under the childhood vaccination programme or one of the catch-up programmes unlikely. Missing information on vaccinations given to older girls is more likely, as women vaccinated in other settings, such as fitness centres and drugstores, were not included in the study cohort. Given that the vaccine was free of charge, the missing information is not expected to cause selection bias. Among the 1420 referred to a diagnostic centre in 2015, 104 referred women were excluded due to missing registration on vaccination. Register errors are likely the reason for missing vaccination registration and since this is rare and unrelated to both exposures and later referral, this missing registration is not considered to have caused selection bias. Mortality rates are low in the studied age groups,23 but 3–5% of 20- to 29-year olds yearly move to another country.23 As relocation may be more likely in women not experiencing adverse events and who have the financial resources to complete such a move, the effect of occupational status of the vaccinated women on the risk of referral could be underestimated. Additionally, we used highest complete education at vaccination as an indicator of SES of the vaccinated women; however, because this measure is correlated with age, some women may have completed additional degrees the years following vaccination. Adjustment for age did, however, not change the associations between educational level and risk of referral. In conclusion, in this nationwide population-based cohort study, we found that being referred to a diagnostic centre due to suspected adverse events following HPV vaccination was associated with having a mother who was unemployed or outside the workforce and low levels of parental education prior to vaccination. Moreover, referrals were associated with unemployment among young adult women the year prior to vaccination. These associations may partly be caused by an increased morbidity prior to vaccination in females of low SES. However, other studies are needed to explain the causal mechanisms between individual and parental SES and risk of referral. Conflicts of interest: None declared. Key points Referral to a diagnostic centre due to suspected adverse events following HPV vaccination was rare (only 0.29%). We found that referral was more likely in girls of parents with low levels of education, in girls of mothers outside the workforce and in girls with unemployed mothers. The associations between socioeconomic factor and risk of referral may partly be caused by increased morbidity prior to vaccination in females of low socioeconomic status. References 1 Schiller JT, Castellsagué X, Garland SM. A review of clinical trials of human papillomavirus prophylactic vaccines. Vaccine  2012; 30: F123– 38. Google Scholar CrossRef Search ADS PubMed  2 Vichnin M, Bonanni P, Klein NP, et al.   An overview of quadrivalent human papillomavirus vaccine safety: 2006 to 2015. Pediatr Infect Dis J  2015; 34: 983– 91. Google Scholar CrossRef Search ADS PubMed  3 Baldur-Felskov B, Dehlendorff C, Munk C, Kjaer SK. Early impact of human papillomavirus vaccination on cervical neoplasia - Nationwide follow-up of young danish women. J Natl Cancer Inst  2014; 106: djt460. 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Association between general practice referral rates and patients’ socioeconomic status and access to specialised health care. A population-based nationwide study. Health Policy (New York)  2009; 92: 180– 6. Google Scholar CrossRef Search ADS   16 Chen E, Matthews KA, Boyce WT. Socioeconomic differences in children’s health: how and why do these relationships change with age? Psychol Bull  2002; 128: 295– 329. Google Scholar CrossRef Search ADS PubMed  17 Pedersen CR, Madsen M. Parents’ labour market participation as a predictor of children’s health and wellbeing: a comparative study in five Nordic countries. J Epidemiol Community Heal  2002; 56: 861– 7. Google Scholar CrossRef Search ADS   18 Sleskova M, Salonna F, Geckova AM, et al.   Unemployment and the health of Slovak adolescents. J Adolesc Health  2006; 38: 527– 35. Google Scholar CrossRef Search ADS PubMed  19 Jensen VM, Rasmussen AW. The Danish Education Registers. Scand J Public Health  2011; 39: 91– 4. 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The European Journal of Public HealthOxford University Press

Published: May 25, 2018

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