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O R I G I N A L A R T I C L E

Fear of hypoglycemia: relationship to hypoglycemic risk

and psychological factors

Therese Anderbro•Linda Gonder-Frederick• Jan Bolinder•Per-Eric LinsRegina Wredling• Erik Moberg•Jan LisspersUnn-Britt Johansson

Received: 15 September 2014 / Accepted: 4 December 2014 / Published online: 21 December 2014 Ó Springer-Verlag Italia 2014

Abstract

Objective The major aims of this study were to examine (1) the association between fear of hypoglycemia (FOH) in adults with type 1 diabetes with demographic, psycholog-ical (anxiety and depression), and disease-specific clinpsycholog-ical factors (hypoglycemia history and unawareness, A1c), including severe hypoglycemia (SH), and (2) differences in patient subgroups categorized by level of FOH and risk of SH.

Research design and methods Questionnaires were mailed to 764 patients with type 1 diabetes including the Swedish translation of the Hypoglycemia Fear Survey (HFS) and other psychological measures including the Perceived Stress Scale, Hospital Anxiety and Depression Scale, Anxiety Sensitivity Index, Social Phobia Scale, and Fear of Complications Scale. A questionnaire to assess hypoglycemia history was also included and A1cmeasures were obtained from medical records. Statistical analyses included univariate approaches, multiple stepwise linear regressions, Chi-square t tests, and ANOVAs.

Results Regressions showed that several clinical factors (SH history, frequency of nocturnal hypoglycemia, self-monitoring) were significantly associated with FOH but R2 increased from 16.25 to 39.2 % when anxiety measures were added to the model. When patients were categorized by level of FOH (low, high) and SH risk (low, high), subgroups showed significant differences in non-diabetes-related anxiety, hypoglycemia history, self-monitoring, and glycemic control.

Conclusion There is a strong link between FOH and non-diabetes-related anxiety, as well as hypoglycemia history. Comparison of patient subgroups categorized according to level of FOH and SH risk demonstrated the complexity of FOH and identified important differences in psychological and clinical variables, which have implications for clinical interventions.

Keywords Type 1 diabetes Hypoglycemia  Fear of hypoglycemia Severe hypoglycemia  Psychological factors

It is well known that depression and anxiety are more prevalent in patients with type 1 diabetes compared to subject without diabetes [1–3] and that psychological Managed by Antonio Secchi.

T. Anderbro (&)

Department of Psychology, Stockholm University, 106 91 Stockholm, Sweden

e-mail: therese.anderbro@psychology.su.se T. Anderbro P.-E. Lins  R. Wredling

Division of Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden L. Gonder-Frederick

Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, VA, USA J. Bolinder E. Moberg

Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Huddinge, Sweden

R. Wredling U.-B. Johansson

Sophiahemmet University College, Stockholm, Sweden J. Lisspers

Department of Social Sciences, Mid Sweden University Campus O¨ stersund, O¨stersund, Sweden

U.-B. Johansson

Department of Clinical Sciences and Education,

So¨dersjukhuset, Karolinska Institutet, Stockholm, Sweden DOI 10.1007/s00592-014-0694-8

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distress has a negative impact on self-management and metabolic control [4,5]. Studies have also found that tar-geting psychological aspects related to diabetes can improve self-management, metabolic control, and also quality of life [6,7]. For many patients with diabetes, fear of complications is a significant aspect of their psycho-logical distress [8, 9] with fear of hypoglycemia (FOH) being common [10–12] and together with fear of vascular complications rated as the most feared complications [13]. FOH may not only negatively influence quality of life (QoL) but also self-management and health outcomes [12], resulting in increased risk of poor metabolic control and long-term complications. Given the impact on those who suffer extreme fear [10, 14, 15], interventions aimed at reducing FOH and its negative effects are needed. How-ever, interventions with empirically supported efficacy are scarce [6,16], which may be due to the complexity of FOH and the lack of knowledge about what factors interven-tion(s) should target. The overall goal of this study was to better understand the complex interactions between FOH, hypoglycemia risk, psychological status, and other clinical variables, and to explore possible targets for interventions. In recent years, intensified insulin therapy has become the standard treatment for type 1 diabetes, which reduces the risk of long-term complications, but also increases the frequency of hypoglycemia, including severe hypoglyce-mia (SH) [17,18]. Several studies have focused on hypo-glycemia risk/occurrence in general and risk/occurrence of SH in particular as important predictors of FOH [12,19–

21], suggesting that intensified insulin therapy may also increase FOH. This research does however not show his-tory of SH uniformly being predictive of FOH, and several studies have found a link between FOH and psychological factors, including trait anxiety [11, 22], extreme fear of self-injecting insulin and self-testing BG [23], and social anxiety [24]. However, little is known about other emo-tional, clinical, and demographic factors that are associated with, contribute to, or exacerbate FOH.

An important consideration is that FOH, unlike many other fears and phobias, is not irrational given that most patients will experience hypoglycemic episodes, including SH. Therefore, some level of concern about SH is appro-priate and adaptive. The higher the level of hypoglycemic risk is, the greater the individuals concern ought to be. However, there can be a disconnect between a patient’s level of hypoglycemic risk and their level of FOH. For example, our previous research found that many patients report high FOH levels even when they have not experi-enced an episode of SH in the previous year [19]. Alter-natively, some patients at high risk of SH show inappropriately low levels of FOH [25]. The present study investigated differences in the psychological and clinical characteristics of subgroups of patients who exhibited

appropriate and inappropriate levels of fear relative to their hypoglycemia history and risk.

Patients and methods

All patients (n = 764) who participated in a previous FOH study [19] were sent a consent form and set of question-naires by mail. Inclusion criteria in the previous study were type 1 diabetes, age C18 years, and diabetes duration C1 year. Potential participants were identified in the local diabetes registries of two university hospitals in Stock-holm, Sweden. The study was approved by the regional ethical review board.

Questionnaires

To measure FOH, we used the Swedish translation of the Hypoglycemia Fear Survey [10,26]. Like the original HFS [1,2], the Swe-HFS consists of two subscales (Worry and Behavior) with 23 items rated on a five-point Likert scale, from 0 (never) to 4 (always). The Worry subscale is composed of 13 items assessing emotional concerns about various aspects of hypoglycemia and its negative conse-quences. The 10-item Behavior subscale measures the extent to which patients engage in various activities to avoid hypoglycemia and its negative consequences. Worry and Behavior subscale scores range from 0 to 52 and 0 to 40, respectively, and the score for the total scale ranges from 0 to 92, with higher scores indicating greater fear. Cronbach’s a 0.92 for the Worry subscale and 0.69 for the Behavior subscale.

Several measures were used to assess different types of psychological stress. The Perceived Stress Scale (PSS) [27] measures the extent to which individuals appraise different life situations as stressful. It contains 14 items measured on a five-point Likert scale (0 = never, 4 = always) with a total score ranging from 0 to 56. Cronbach’s a 0.94.

The Social Phobia Scale (SPS) [28] has 20 items and measures anxiety in different social situations. Items are rated on a five-point Likert scale from 0 (does not apply to me) to 4 (applies completely to me) with a total score ranging from 0 to 80.

The Hospital Anxiety and Depression Scale (HADS) measures depression and anxiety in medical populations. The 14 items are assessed on a four-point Likert scale from 0 (not at all) to 3 (most of the time) [29], with total scores for the depression and anxiety subscales ranging from 0 to 21. Cronbach’s a fort total HADS 0.91.

The Anxiety Sensitivity Index (ASI) [30] measures fear of anxiety-related symptoms, with 16 items rated on a five-point Likert scale (0 = not at all and 4 = very much), with total scores ranging from 0 to 64.

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The Fear of Complications Questionnaire (FCQ) [8] contains 15 items measuring fear of long-term complica-tions. Items are rated on a four-point Likert scale from 0 (never) to 3 (always), with total scores ranging from 0 to 45. Cronbach’s a 0.94.

Alcohol habits were measured using the first two ques-tions measuring frequency and amount of alcohol from AUDIT (The Alcohol Use Disorders Identification Test) [31]. Exercise habits were measured with three items assessing frequency and intensity of exercise, which were previously used in a study of exercise habits and health among adults in Sweden [32]. Alcohol and exercise were assessed as they increase the risk of hypoglycemia.

To obtain a measure of long-term glycemic control, the median value of all A1c(Mono S) test results recorded in patient medical charts during the past 2 years was computed.

Patients also completed a diabetes history questionnaire assessing clinical variables regarding frequency and severity of hypoglycemia, hypoglycemic unawareness, and daily self-monitoring of blood glucose (SMBG) over the past 12 months [33]. Frequency of mild and moderate hypoglycemia was categorized as low (never—3 episodes/ month) and high (C1 episode/week), frequency of noctur-nal episodes as low (0–5 episodes/year) and high (C1 episode/month), and frequency of SH as low (0 episodes), high (C1 episode). Emergency room (ER) visits were categorized as low (0 times) and high (C1 time). Hypo-glycemic unawareness was measured on a categorical scale by asking ‘‘In the past 12 months how often has your SMBG shown \4 mmol/l without you noticing any symptoms of hypoglycemia?’’ where B5 times was cate-gorized as low and C1–3 times/month was catecate-gorized as high. Frequency of SMBG was categorized as low (never— 3 days/week) and high (daily), and frequency of nocturnal SMBG was categorized as low (B3 nights/month) and high (C2 nights/week). Number of nights spent alone per week was also assessed since previous HFS research identified a factor reflecting fear of being alone when hypoglycemia occurs [19].

Statistical analysis

Statistical analysis was performed using PASW 18.0 soft-ware for Windows (SPSS Inc., Chicago, IL, USA). Descriptive statistics were used for demographic and clinical characteristics. Missing values were imputed using the Expectation–Maximization algorithm for all patients. Rates of missing values were overall very low, 1.7–2.9 %, except for item 19 in the HFS (‘‘Having a reaction while driving’’), which had 7.4 % missing values. To investigate which variables were significantly associated with overall FOH, multiple linear regression analyses were performed

using the sum score of HFS total as dependent variables. The regression models were obtained by entering the variables in three blocks with the first block containing all demographic variables, the second all clinical variables, and the third psychological variables. Within each of the three blocks, forward stepwise regressions identified those variables significantly associated with the HFS scores. Data were checked for multicollinearity using the variance inflation factor \4 and tolerance values [0.20 as criteria. To validate the models, standard residuals were checked for normal distribution.

Differences between groups were analyzed using Chi-square tests, unpaired t tests, or ANOVAs. Psychological and clinical characteristics associated with FOH were compared across two patient subgroups representing the highest and lowest percentiles for total HFS scores—those showing high FOH (scores C75th percentile) and low FOH (scores B25th percentile). These low and high FOH groups were further divided into two groups representing SH risk—those who experienced SH in the past year (high risk) and those who did not (low risk). This allowed comparisons across four independent patient groups cate-gorized by level of FOH and SH risk.

Results

A total of 469 (61 %) patients (responders) returned questionnaires. Mean age was 47 years, mean diabetes duration was 31.0 years, and mean A1cwas 6.9 % Mono S (61 mmol/mol). There were some minor differences between responders and non-responders with regard to demographic and clinical characteristics (Table1).

Total HFS score was used as a continuous dependent variable in regression analysis (Table2). Gender was the only demographic variable associated with HFS scores, with women (m = 14.6, SD = 10.5) scoring higher than men (m = 11.4, SD = 9.2) on the Worry (t = 3.397, p = 0.001), but not the Behavior subscale (m = 18.8, SD = 5.9 for women; m = 18.1, SD = 6.1 for men) (t = 1.121, p = 0.263). Regression analysis indicated that several clinical variables were positively associated with HFS scores, including frequency of SH, nocturnal hypo-glycemia, and SMBG, as well as the number of symptoms experienced during mild hypoglycemia. Three psycholog-ical variables were also positively associated with HFS scores, including the ASI, HADS Anxiety subscales, and the SPS. Adding the psychological variables to the model increased the variance explained from 16.2 to 39.2 %. Zero-order correlations for all independent variables (IV) are found in Table3.

The next analyses compared clinical and psychological variables across the four FOH/SH risk groups. The number

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of patients from the total sample (n = 469) categorized as low versus high FOH was 161 (34.3 %) and 152 (32.4 %), respectively. The number categorized as low versus high SH risk was 341 (75 %) and 118 (25 %). Tables 4 and5

show the number of patients categorized into each of the four subgroups based on level of FOH and SH risk. The majority of patients fell into the low FOH/low SH risk (43 %) and the high FOH/low SH risk (32 %) groups, while fewer fell into the high FOH/high SH risk (17 %) and the low FOH/high SH risk (8 %) groups.

ANOVAs showed a significant subgroup effect for all psychological measures, as well as for number of symp-toms during mild hypoglycemia and A1c(Table4). For all anxiety-related measures, both groups with high FOH showed significantly higher scores than the low FOH groups, regardless of SH risk (all p’s B 0.001). The same difference was found for depression, with both high FOH groups showing significantly higher scores on the HADS depression subscale. No subgroup effect was found for frequency of exercise or nights spent alone.

Comparisons of clinical variables between the four subgroups also yielded a number of differences.

High FOH/high SH risk: Patients in the high FOH/high SH risk group reported the highest frequency of moderate

Table 1 Demographic and clinical characteristics of responders and non-responders All patients n = 744 Responders n = 469 Non-responders n = 275 p Mean Median SD 25th percentile 75th percentile Mean Median SD 25th percentile 75th percentile Mean Median SD 25th percentile 75th percentile HbA 1c 7.0 6.9 1.1 6.3 7.7 6.9 6.9 1.0 6.3 7.6 7.1 7 1.2 6.4 7.8 0.031 Age (years) 46.3 45 13.6 36 57 46.8 46 14.0 35 58 44.9 43 12.8 36 55 0.037 Duration (years) 30.3 29 14.0 20 40 31.0 31 14.2 19 41 28.9 28 13.9 19 38 0.032 Gender (% female) 50 49.5 50.5 0.864

Table 2 Demographic, clinical, and psychological variables related to fear of hypoglycemia (HFS total)

Variables B Step 1 B Step 2 B Step 3 Step 1: Demographic variables

Gender 0.151* 0.082** 0.009** Step 2: Clinical Frequency of nocturnal hypoglycemia 0.185** 0.083** Frequency of SH 0.204** 0.146** Frequency of SMBG 0.184** 0.179** Number of symptoms during

mild hypoglycemia

0.178** 0.074** Step 3: Psychological variables

Anxiety Sensitivity Index 0.335**

HADS Anxiety Scale 0.174**

Social Phobia Scale 0.142**

Model summary Model F 7.217** 13.030** 26.061** (df) (1, 310) (5, 306) (8, 303) R2 0.023 0.176 0.408 Adjusted R2 0.020 0.162 0.392 DR2 0.023** 0.153** 0.232**

Results are from stepwise multiple linear regression analyses. Only variables significantly contributing to the model are displayed (vari-ables selected using forward stepwise regression). All vari(vari-ables are simultaneously adjusted for

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and nocturnal hypoglycemia, ER visits due to hypoglyce-mia, hypoglycemic unawareness, and daily SMBG (see Table5). A1cwas also significantly lower in this group as compared to the low FOH/low SH risk group (p = 0.050). High FOH/low SH risk: In addition to higher anxiety and depression scores, patients in the high FOH/low SH risk group reported more symptoms during mild hypogly-cemia than both low FOH groups. This group also reported more hypoglycemic symptoms during hyperglycemia compared to other subgroups and the lowest frequency of alcohol consumption.

Low FOH/low SH risk: In addition to higher A1clevels, these patients reported a lower frequency of moderate and nocturnal hypoglycemia, as well as daily SMBG compared to the high FOH/high SH risk group.

Low FOH/high SH risk: There were no differences between patients in this subgroup and others on any clinical variables, but as noted earlier these patients showed lower anxiety and depression scores than both high FOH groups.

Discussion

These findings highlight the complexity of FOH and its relationship with psychological and diabetes-related clinical factors. Regressions showed that clinical variables, includ-ing hypoglycemia history and awareness, were significantly

associated with FOH, but adding anxiety-related factors to the model increased the explained variance from 16 to 39 %. This finding indicates a strong relationship between FOH, other diabetes-related fears, and non-diabetes-related types of anxiety (e.g., social). However, no causal conclusions can be drawn from these cross-sectional findings, and it remains unclear whether a tendency toward anxiety across a broad range of life situations increases vulnerability for FOH, or vice versa. Fear of anxiety symptoms (ASI) was the psy-chological factor most strongly associated with FOH. Because anxiety symptoms overlap to a large extent with autonomic hypoglycemia symptoms, which likely trigger a fear response in many people with diabetes, the ASI and HFS may in part measure similar constructs. However, it is important to know that some patients may fear not only the consequences of hypoglycemia but also the symptoms themselves. Elevated depression symptoms found in patients with high FOH may be secondary to high levels of anxiety. Data also indicate that FOH is associated with reduced QoL which can increase depression [3] and a link between FOH and depressive symptoms was found in par-ents of children with diabetes [28]. Demographic variables were unrelated to FOH in this study, with the exception of higher scores in women on the Worry subscale, replicating previous findings [19,20].

This study also identified important differences in sub-groups of patients reporting low and high levels of FOH Table 3 Zero-order correlations between IV in the regression analysis

HFS total HADS Anxiety Anxiety Sensitivity Index Number of symptoms during mild HG Social Phobia Scale Frequency of SMBG Frequency of severe hypoglycemia Frequency of nocturnal hypoglycemia Gender a 0.89 0.483** 0.637** 0.176** 0.458** 0.177** 0.209** 0.188** 0.150** HFS total a 0.83 0.612** 0.232** 0.629** 0.034 0.087 0.251** 0.173** HADS Anxiety a 0.90 0.192** 0.628** 0.047 0.146** 0.118* 0.096* Anxiety Sensitivity Index 0.257** -0.040 -0.071 0.098* 0.117* Number of symptoms during mild HG a 0.82 0.059 0.080 0.198** 0.187** Social Phobia Scale 0.018 0.150** 0.164** Frequency of SMBG 0.018 -0.044 Frequency of severe hypoglycemia 0.139** Frequency of nocturnal hypoglycemia Gender ** Correlation is significant at the 0.01 level

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Table 4 Results from ANOVAs for demographic, clinical, and psychological measures in the four subgroups Low fear/low risk (n = 136, 43 %) Low fear/high risk (n = 25, 8 % ) High fear/low risk (n = 101, 32 %) High fear/high risk (n = 52, 17 %) F (df ) p M (SD) M (SD) M (SD) M (SD) Age 44.6(13.4) 48(13.5) 47.5(15.2) 50.0(11.7) 2.25 (3, 310) 0.08 A1c 7.1 %, (63 mmol/mol) (0.9) b 7.0 %, (62 mmol/mol) (1.3) 6.9 %, (61 mmol/mol) (1.0) 6.6 %, (58 mmol/mol) (1.2) a 2.58 (3, 301) 0.05 Number of symptoms during mild hypoglycemia 3.2 (1.7) b 3.1 (2.1) b 4.3 (2.0) a 3.4 (2.1) 6.61 (3, 310) B 0.001 Anxiety Sensitivity Index (Sumscore 0–64) 6.9 (5.7) b 6 (5.8) b 20.5 (10.4) a 24.4 (13.7) a 69.26 (3, 288) B 0.001 Perceived Stress Scale (Sumscore 0–56) 26 (9.0) b 27.2 (7.1) b 33.6 (7.5) a 34 (8.1) a 6.89 (3, 296) B 0.001 Hospital Anxiety and Depression Scale—Anxiety subscale, Sumscore 0–21 3 (2.8) b 3.2 (3.4) b 7.3 (4.5) a 8.4 (5.8) a 33.46 (3, 288) B 0.001 Hospital Anxiety and Depression Scale—Depression subscale, Sumscore 0–21 2.3 (2.5) b 2.8 (2.9) b 5.4 (3.8) a 6.1 (4.7) a 23.41 (3, 302) B 0.001 Social Phobia Scale (Sumscore 0–80) 4 (6.5) b 2.1 (3.8) b 19.3 (12.3) a 15.4 (16.1) a 22.83 (3, 296) B 0.001 Fear of Complications Scale (Sumscore 0–45) 10.5 (6.5) b 3.1 (6.4) b 19.5 (8.5) a 21.9 (10.4) a 38.39 (3, 295) B 0.001 Means marked with bold text and with different superscripts are significantly different (p \ 0.05; Tukey HSD ) o r indicate where the largest difference between actual frequency and expected frequencies are for factors with a significant difference

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relative to their personal hypoglycemia risk, which appear to have important implications for interventions. Anxiety measure scores were equally elevated in high FOH patients, regardless of actual SH risk. Patients in the high FOH/high SH risk group were also characterized by clin-ical variables associated with increased SH risk, including more frequent moderate and nocturnal hypoglycemia, ER visits, and hypoglycemic unawareness. This patient group also reported a higher frequency of daily and nocturnal SMBG, an appropriate and adaptive response to greater hypoglycemic risk. Individuals in the high FOH/high SH risk group would likely benefit most from clinical inter-ventions aimed at reducing their elevated SH risk. These might include changes in diabetes management, such as utilization of insulin pump therapy and/or continuous glu-cose monitoring systems [34], as well as patient education regarding hypoglycemia prevention. Interventions that increase hypoglycemic symptom awareness, such as scru-pulous avoidance of even mild low BG excursions or Blood Glucose Awareness Training programs (BGAT), may also be beneficial [35].

In contrast, the high FOH/low SH risk group was not characterized by clinical factors indicative of problematic hypoglycemia but rather by high levels of diabetes-related and other anxiety. Given high FOH levels in spite of low levels of hypoglycemic risk, these patients might benefit from interventions aimed at anxiety reduction, including

exposure therapy, relaxation training, and coping skills enhancement [10,30,31]. High FOH/low SH risk patients also reported experiencing a higher number of hypogly-cemic symptoms, with both low and high BG levels. This suggests that these patients may also benefit from programs that decrease sensitivity to adrenergic symptoms, as well as interventions that improve recognition of hypoglycemic symptoms.

Patients in the low FOH/low SH risk group had sig-nificantly higher A1c levels than those in the high FOH/ high SH risk group, fewer moderate and nocturnal hypoglycemic episodes, and a lower frequency of SMBG. Given their reduced risk of hypoglycemia, lower levels of FOH would appear to be appropriate for these patients. However, the higher HbA1c levels found in this group indicate that these patients may be at higher risk of a less desirable level of diabetes control. It is possible that these patients experience less concern about hypo-glycemia because their typical BG levels are more likely to be high than low. Some of these individuals may represent those patients who cope with FOH and reduce hypoglycemic risk by maintaining undesirably high BG levels. For this patient group, interventions aimed at improving diabetes management and control, without increasing hypoglycemia risk, may be most beneficial, as well as training in more adaptive methods for coping with FOH [36].

Table 5 Results from the Chi-square tests for demographic, clinical, and psychological measures in the four subgroups Low fear/low risk

(n = 136, 43 %)

Low fear/high risk (n = 25, 8 %)

High fear/low risk (n = 101, 32 %)

High fear/high risk (n = 52, 17 %) V2(df) p n (%) n (%) n (%) n (%) Gender (male) 75 (55) 16 (64) 34 (33.7) 26 (50) 13.75 (3, 314) 0.003 Frequency of nocturnal SMBG (high) 7 (5.1) 7 (28) 16 (15.8) 14 (26.9) 20.41 (3, 314) 0.000 Frequency of SMBG (high) 92 (67.6) 16 (65) 81 (80.2) 45 (86.5) 10.51 (3, 314) 0.015 Frequency of mild HG (high) 70 (51.4) 16 (64) 57 (56.4) 37 (71.2) 6.97 (3, 312) 0.073 Frequency of moderate HG (high) 32 (23.5) 8 (32) 35 (34.7) 23 (44.2) 8.29 (3, 312) 0.040 Frequency of nocturnal HG (high) 33 (24.3) 7 (28) 43 (42.6) 26 (50) 14.19 (3, 304) 0.003 Hypoglycemic unawareness 53 (39) 13 (52) 51 (50.5) 37 (71.2) 16.43 (3, 309) 0.001 Symptoms of hypoglycemia

during hyperglycemia (high)

26 (19.1) 5 (20) 38 (37.6) 13 (25) 10.67 (3, 309) 0.014 Visits to emergency department

(high)

1 (0.7) 5 (20) 2 (2) 21 (40.4) 81.71 (3, 314) 0.000 Frequency of alcohol

consumption (high)

111 (81.2) 20 (80) 59 (58.4) 34 (65.4) 19.62 (3, 310) 0.000 Frequency of exercise (high) 93 (68.4) 20 (80) 76 (75.2) 32 (61.5) 2.59 (3, 284) 0.458 Frequency of nights alone

(high)

53 (39) 11 (44) 46 (45.5) 24 (46.2) 1.78 (3, 308) 0.620

Means marked with bold text and with different superscripts are significantly different (p \ 0.05; Tukey HSD) or indicate where the largest difference between actual frequency and expected frequencies is for factors with a significant difference

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Perhaps most puzzling and problematic is the low FOH/ high SH risk group. These patients have realistic reasons to be concerned about hypoglycemia; therefore, higher FOH levels would seem more appropriate. Recent research into patients with hypoglycemic unawareness has identified a subgroup of individuals who appear to lack adequate concern about their high risk, as well as willingness to make regimen changes to reduce risk [32–34]. There is evidence that these attitudinal and behavioral features may be related to neurological differences compared to those with intact awareness [25]. These hypoglycemic unaware patients who exhibit inadequate levels of concern about their risk may fall into the low FOH/high SH group. However, this study did not find more hypoglycemic unawareness in this group in this study, although it is possible that the small number of individuals in this sub-group resulted in insufficient statistical power to detect differences. More research is needed to identify patient characteristics associated with inappropriately low levels of FOH and guide intervention development. There is encouraging research suggesting that cognitive-behavioral therapy may effectively alter the maladaptive beliefs [e.g., ‘‘It is not a problem to lose awareness’’, ‘‘I can function OK with low (below 3) blood sugar levels’’ [25]] that appear to contribute to inappropriate low FOH in patients with high SH risk [37].

The above conclusions should be interpreted with caution, bearing in mind the preliminary nature of these findings as well as methodological limitations, including the moderate response rate (61 %). Another sampling issue is that the majority of the patients in this study were, by our definition, at low risk of SH. Future studies investigating FOH relative to hypoglycemic history/risk should attempt to recruit more patients who experience frequent SH. In addition, our definitions and measures of hypoglycemic and SH history may not completely capture all of the aspects of hypoglycemic risk that contribute to FOH. For example, the degree to which past hypoglyce-mia episodes and/or their consequences were psycholog-ically or physpsycholog-ically traumatic was not assessed, even though this likely plays a major role in the development of FOH. In spite of these limitations, however, these findings appear to have important implications for future research and clinical interventions. A variety of factors need to be considered in order to understand the psy-chological and clinical implications of FOH, and there is not a ‘‘one size fits all’’ intervention for patients with problematic FOH and hypoglycemia. Rather, these results suggest that a variety of different treatment approaches are needed to address the complex interactions between FOH, emotional well-being, diabetes management, and glycemic control.

Acknowledgments This study was funded by Sophiahemmet Uni-versity College, the Foundation for Medical Research at Sophia-hemmet, the Swedish Diabetes Federation, and the Bert von Kantzow Foundation. The authors would like to thank Katarina Selling, Stat-isticon for statistical support. No potential conflicts of interest rele-vant to this article were reported. T.A. researched and interpreted the data and wrote the manuscript. J.L., E.M, L.G-F, and U-B.J. inter-preted the data and reviewed/edited the manuscript, J.B, P-E.L., and R.W contributed to discussion and reviewed/edited the manuscript. All authors reviewed, commented on, and accepted the manuscript. T.A. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Conflict of interest Therese Anderbro, Linda Gonder-Frederick, Jan Bolinder, Per-Eric Lins, Regina Wredling, Erik Moberg, Jan Lisspers and Unn-Britt Johansson declare that they have no conflict of interest.

Ethical standard All human studies have been reviewed by the appropriate ethics committee and have therefore been performed in accordance with the ethical standards laid down in an appropriate version of the 1964 Declaration of Helsinki.

Human and animal rights disclosure All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Informed consent disclosure Informed consent was obtained from all patients for being included in the study.

References

1. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ (2001) The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care 24(6):1069–1078

2. Collins MM, Corcoran P, Perry IJ (2009) Anxiety and depression symptoms in patients with diabetes. Diabet Med 26(2):153–161 3. Lloyd CE, Dyer PH, Barnett AH (2000) Prevalence of symptoms

of depression and anxiety in a diabetes clinic population. Diabet Med 17(3):198–202

4. Grigsby AB, Anderson RJ, Freedland KE, Clouse RE, Lustman PJ (2002) Prevalence of anxiety in adults with diabetes: a sys-tematic review. J Psychosom Res 53(6):1053–1060

5. Katon W, von Korff M, Ciechanowski P, Russo J, Lin E, Simon G et al (2004) Behavioral and clinical factors associated with depression among individuals with diabetes. Diabetes Care 27(4):914–920

6. Amsberg S, Anderbro T, Wredling R, Lisspers J, Lins PE, Ad-amson U et al (2009) A cognitive behavior therapy-based inter-vention among poorly controlled adult type 1 diabetes patients— a randomized controlled trial. Patient Educ Couns 77(1):72–80 7. Forlani G, Nuccitelli C, Caselli C, Moscatiello S, Mazzotti A,

Centis E et al (2013) A psychological support program for indi-viduals with type 1 diabetes. Acta Diabetol 50(2):209–216 8. Taylor EP, Crawford JR, Gold AE (2005) Design and

develop-ment of a scale measuring fear of complications in type 1 dia-betes. Diabetes Metab Res Rev 21(3):264–270

9. Olsen M, Anderbro T, Amsberg S, Leksell J, Moberg E, Lisspers J, Gudbjo¨rnsdottir S, Johansson U-B (2014) Psychometric prop-erties of the Swedish version of the fear of complications ques-tionnaire. Open J Endocr Metab Dis 4(4):69–76

(9)

10. Cox DJ, Irvine A, Gonder-Frederick L, Nowacek G, Butterfield J (1987) Fear of hypoglycemia: quantification, validation, and utilization. Diabetes Care 10(5):617–621

11. Irvine AA, Cox D, Gonder-Frederick L (1992) Fear of hypo-glycemia: relationship to physical and psychological symptoms in patients with insulin-dependent diabetes mellitus. Health Psychol 11(2):135–138

12. Wild D, von Maltzahn R, Brohan E, Christensen T, Clauson P, Gonder-Frederick L (2007) A critical review of the literature on fear of hypoglycemia in diabetes: implications for diabetes management and patient education. Patient Educ Couns 68(1):10–15

13. Pramming S, Thorsteinsson B, Bendtson I, Binder C (1991) Symptomatic hypoglycaemia in 411 type 1 diabetic patients. Diabet Med 8(3):217–222

14. Clarke WL, Gonder-Frederick A, Snyder AL, Cox DJ (1998) Maternal fear of hypoglycemia in their children with insulin dependent diabetes mellitus. J Pediatr Endocrinol Metab 11(Suppl 1):189–194

15. Cox DJ, Gonder-Frederick L, Antoun B, Clarke W, Cryer P (1990) Psychobehavioral metabolic parameters of severe hypo-glycemic episodes. Diabetes Care 13(4):458–459

16. Cox DJ, Gonder-Frederick L, Polonsky W, Schlundt D, Kovat-chev B, Clarke W (2001) Blood glucose awareness training (BGAT-2): long-term benefits. Diabetes Care 24(4):637–642 17. The Diabetes Control and Complications Trial Research Group

(1993) The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 329(14): 977–986

18. Nathan DM, Cleary PA, Backlund JY, Genuth SM, Lachin JM, Orchard TJ et al (2005) Intensive diabetes treatment and car-diovascular disease in patients with type 1 diabetes. N Engl J Med 353(25):2643–2653 PMCID: 2637991

19. Anderbro T, Amsberg S, Adamson U, Bolinder J, Lins PE, Wredling R et al (2010) Fear of hypoglycaemia in adults with type 1 diabetes. Diabet Med 27(10):1151–1158

20. Gonder-Frederick LA, Schmidt KM, Vajda KA, Greear ML, Singh H, Shepard JA et al (2011) Psychometric properties of the hypoglycemia fear survey-ii for adults with type 1 diabetes. Diabetes Care 34(4):801–806 PMCID: 3064031

21. Schopman JE, Geddes J, Frier BM (2011) Frequency of symp-tomatic and asympsymp-tomatic hypoglycaemia in type 1 diabetes: effect of impaired awareness of hypoglycaemia. Diabet Med 28(3):352–355

22. Polonsky WH, Davis CL, Jacobson AM, Anderson BJ (1992) Correlates of hypoglycemic fear in type I and type II diabetes mellitus. Health Psychol 11(3):199–202

23. Mollema ED, Snoek FJ, Ader HJ, Heine RJ, van der Ploeg HM (2001) Insulin-treated diabetes patients with fear of self-injecting

or fear of self-testing: psychological comorbidity and general well-being. J Psychosom Res 51(5):665–672

24. Di Battista AM, Hart TA, Greco L, Gloizer J (2009) Type 1 diabetes among adolescents: reduced diabetes self-care caused by social fear and fear of hypoglycemia. Diabetes Educ

25. Rogers HA, de Zoysa N, Amiel SA (2012) Patient experience of hypoglycaemia unawareness in type 1 diabetes: are patients appropriately concerned? Diabet Med 29(3):321–327

26. Anderbro T, Amsberg S, Wredling R, Lins PE, Adamson U, Lisspers J et al (2008) Psychometric evaluation of the Swedish version of the Hypoglycaemia Fear Survey. Patient Educ Couns 73(1):127–131

27. Cohen S, Kamarck T, Mermelstein R (1983) A global measure of perceived stress. J Health Soc Behav 24(4):385–396

28. Mattick RP, Clarke JC (1998) Development and validation of measures of social phobia scrutiny fear and social interaction anxiety. Behav Res Ther 36(4):455–470

29. Lisspers J, Nygren A, Soderman E (1997) Hospital Anxiety and Depression Scale (HAD): some psychometric data for a Swedish sample. Acta Psychiatr Scand 96(4):281–286

30. Reiss S, Peterson RA, Gursky DM, McNally RJ (1986) Anxiety sensitivity, anxiety frequency and the prediction of fearfulness. Behav Res Ther 24(1):1–8

31. Babor TF, Dolinsky ZS, Meyer RE, Hesselbrock M, Hofmann M, Tennen H (1992) Types of alcoholics: concurrent and predictive validity of some common classification schemes. Br J Addict 87(10):1415–1431

32. Engstro¨m L-M, Ekblom B, Forsberg A, von Koch M, Seger J (1993) Motionsvanor, fysisk prestationsfo¨rma˚ga och ha¨lsotill-sta˚nd bland svenska kvinnor och ma¨n i a˚ldrarna 20–65 a˚r. Stockholm; Contract no.: document number

33. Wredling R (1991) On the management of insulin dependent diabetes mellitus. Karolinska Institutet, Stockholm

34. Hommel E, Olsen B, Battelino T, Conget I, Schutz-Fuhrmann I, Hoogma R et al (2014) Impact of continuous glucose monitoring on quality of life, treatment satisfaction, and use of medical care resources: analyses from the SWITCH study. Acta Diabetol 51(5):845–851 PMCID: 4176956

35. Briscoe VJ, Davis SN (2006) Hypoglycemia in type 1 and type 2 diabetes: physiology, pathophysiology, and management. Clin Diabetes 24(3):115–121

36. Byrne M, Newell J, Coffey N, OH MC, Cooke D, Dinneen SF (2012) Predictors of quality of life gains among people with type 1 diabetes participating in the Dose Adjustment for Normal Eating (DAFNE) structured education programme. Diabetes Res Clin Pract 98(2):243–248

37. de Zoysa N, Rogers H, Stadler M, Gianfrancesco C, Beveridge S, Britneff E et al (2013) A psychoeducational programme to restore hypoglycemia awareness: the DAFNE-HART pilot study. Dia-betes Care 37(3):863–866

References

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