Women & Health, 55:134–151, 2015 Copyright © Taylor & Francis Group, LLC ISSN: 0363-0242 print/1541-0331 online DOI: 10.1080/03630242.2014.979967
The Relation of Weight to Women’s Health: A Matched Sample Study from Austria NATHALIE T. BURKERT, Mag, ÉVA RÁSKY, Dr, FRANZISKA GROßSCHÄDL, BSc, MSc, Dr, JOHANNA MUCKENHUBER, MMag, and WOLFGANG FREIDL, Dr Institute of Social Medicine and Epidemiology, Medical University Graz, Graz, Austria
While being underweight, overweight, or obese has been associated with higher rates of morbidity and mortality, such relations have not been studied in Austrian women. Therefore, the aim of this study was to analyze differences in health, health behaviors, and quality of life among women of various weight status categories, using data from the Austrian Health Interview (AT-HIS) 2006/07. First, women between 20 and 60 years of age, from four different weight status groups (underweight, normal weight, overweight, and obese) were matched case to case on age and socioeconomic status. After matching, the total number of women included in the analyses was 516 ( N = 129 per). Differences in health status among women in different weight status categories were calculated using multiple conditional logistic regression analyses. Compared to females in the other three groups, women with normal weight had the best state of health: they had better self-reported health, suffered from fewer chronic conditions (e.g., sacrospinal complaints or migraines), and needed medical treatment less often. Moreover, they had better self-reported quality of life. In contrast, women who were underweight or obese showed worse health than women of normal weight. Appropriate health programs for weight risk groups are needed. KEYWORDS weight status, BMI, health-related behavior, health, quality of life
Received July 26, 2013; revised February 26, 2014; accepted March 10, 2014. Address correspondence to Nathalie T. Burkert, Mag, Institute of Social Medicine and Epidemiology, Medical University Graz, Universitaetsstrasse 6/I, Graz A-8010, Austria. E-mail: [email protected]
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INTRODUCTION In most countries, a double burden exists related to weight—while the prevalence of overweight and obesity is rising, the prevalence of underweight is still high. An inverse relationship between educational level and body weight has been established (Ali and Lindström 2006; Großschädl, Haditsch, and Stronegger 2012; Kilicarslan et al. 2006; Roskam et al. 2010). The risk of obesity also increases with lower income (Amarasinghe et al. 2009) and is inversely associated with socioeconomic status (SES) (Burkert et al. 2012a; WHO 1998), even after adjusting for age (Brennan et al. 2009; Großschädl and Stronegger 2013). Results of the 2002/03 World Health Survey showed that in most urbanized countries, women with greater educational attainment had a lower body mass index (BMI) (Fleischer, Diez Roux, and Hubbard 2012). Additionally, BMI differed by race/ethnicity (Mack et al. 2004). Both a low BMI (underweight) as well as a high BMI (overweight and obesity) have been associated with poorer health (Franco et al. 2012; Ha do et al. 2011; Hu 2003; Khan and Kraemer 2009). Obesity has also been associated with greater multi-morbidity and a higher prevalence of chronic conditions, including hypertension, diabetes mellitus, and cardiovascular diseases (CVD) (Barnes 2011; Booth, Prevost, and Gulliford 2013; Burkert et al. 2013; Hu 2003; WHO 2012). In contrast, underweight has been related to bradycardia, hypotension, hypothermia, and osteopenia (Lemberg 1999). Moreover, women who were underweight, overweight, or obese have self-reported poorer health than women with normal weight (Ali et al. 2006). Especially for CVD, a J-shaped relationship between BMI and CVD-specific mortality has been found (Berrington de Gonzalez et al. 2010; Dudina et al. 2011), and frailty has been related to both weight loss and heart disease (Von Haehling et al. 2013). Additionally, all-cause mortality was significantly increased in underweight and obese persons (Bessonova et al. 2011) and lowest in persons with a normal BMI between 20.0 and 24.9 kg/m2 (Berrington de Gonzalez et al. 2010). Extreme body weights were also associated with more hospital stays compared to individuals with normal weight (Wulff and Wild 2011). Moreover, quality of life (QOL) has been associated with body weight, although the effect was appeared to be modified by age (Branca, Nikogosian, and Lobstein 2007; Brennan et al. 2009; Cash et al. 2011; Gallon and Wender 2012; Garner et al. 2012; Ha do et al. 2011; Khan and Kraemer 2009; Sirtori et al. 2012). Underweight in women was associated with higher QOL at younger ages but was related to lower QOL at older ages (Garner et al. 2012). Nevertheless, compared to normal-weight women the mental health of underweight women was impaired, even after controlling for demographic characteristics and lifestyle factors (Mond et al. 2011). The highest QOL score has been observed among women with a BMI of 24.5 kg/m2 (Søltoft, Hammer, and Kragh 2009).
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However, not only body weight, but also lifestyle factors had an influence on health (Bauer et al. 2009). Lifestyle factors, which have been associated with health risk, include tobacco smoking, alcohol consumption, inadequate nutrition, and physical inactivity (Branca, Nikogosian, and Lobstein 2007). All of these risk factors were more prevalent in women who were overweight/obese (Ali et al. 2006). The health risk of alcohol consumption is more complex. While moderate alcohol drinking has been related to a lower mortality rate (Adler and Newman 2002), both abstinence and excessive alcohol consumption are detrimental to health (Mackenbach 2006). Pack-years of smoking, never drinking or excessive alcohol intake, as well as physical inactivity have been associated with increased mortality. Moreover, the combination of these factors (smoking, physical inactivity, never drinking or excessive alcohol intake) with a BMI outside the normal range has been associated with an increased risk of mortality by nearly 60% (Iversen et al. 2010). In conclusion, extremes of body weight have been associated with poorer health. To our knowledge no prior study in Austria has compared the health relations of underweight, normal weight, overweight, and obesity to women’s health, health behavior, and QOL. Therefore, the aim of this study was to analyze differences in terms of health-related behavior, health, and QOL of women with different BMIs, matched according to their age and socioeconomic status.
MATERIAL AND METHODS Study Population The sample for this study was taken from the Austrian Health Interview Survey (AT-HIS), which was conducted between 2006 and 2007 (Klimont, Kytir, and Leitner 2007). The AT-HIS is a standardized survey conducted at regular intervals in Austria (currently every 8 years). The AT-HIS is part of the European Health Interview Survey (E-HIS; http://www.euhsid.org), an important survey of high quality. The participants included a representative sample of the Austrian population. The reference population for the survey included all persons who were listed in the register of residence of Austria who were aged 15 years or older. To get a representative sample, the respondents were stratified according to Austria’s different geographic regions, and the sampling was weighted according to the number of the inhabitants in the specific regions. The interviews were conducted faceto-face by persons engaged by the Austrian Statistic Agency. To ensure that all interviews were conducted in the same way, interviewers underwent 1 day of training and were given guidelines in conducting the survey. To ensure interviewer consistency, time measurement, non-response analysis, and analysis of erroneous dialogs were performed. Additionally, the work of the interviewers was overseen by field supervisors.
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Overall, 15,474 participants aged 15 years and older were interviewed through computer-assisted personal interviews (CAPI; 54.7% female). All participants were first contacted and informed about the survey by telephone. If they agreed to take part, an appointment for the CAPI was arranged. No minors or children and only those respondents who could provide information personally were included in the study. Respondents who did not speak the German language, who could not be reached after three attempts to contact them, or who were in a hospital at the time of the interview were excluded. The response rate of the AT-HIS was 63.1%. The study was carried out in compliance with the declaration of Helsinki, and the ethics committee of the Medical University of Graz approved this study protocol (EK-number: 24-288 ex 11/12). Verbal informed consent was obtained from all participants, witnessed and formally recorded before the interview. Because weight has a different influence on health in men and women (Hemmelmann et al. 2010; Hüsler et al. 2010; Kuczmarski and Flegal 2000; Nysom et al. 2001), we restricted our analyzed sample to women. Moreover, because the relation of weight to health in adolescents is different, and percentile curves are used to define extremes of body weight at these younger ages (De Onis et al. 2007), we only analyzed data from adult women aged 20 years and over. Additionally, we only analyzed data from adults who were younger than 60 years because weight increases in both men and women with age (Micozzi and Harris 1990), and the relation of BMI to disease and mortality risk differs in the elderly (Dorner and Rieder 2010; Volkert 2006). To conclude, the present analyses were carried out for women aged 20 through 59 years, stratified by their weight status. The classification for underweight, normal weight, overweight, and obesity were made according to the World Health Organization (WHO 2000) [underweight (BMI < 18.5 kg/m2 ), normal weight (BMI ≥ 18.5 kg/m2 and 11).
Differences in Health Behavior Among Underweight, Overweight, or Obese and Normal-Weight Women Our analyses showed that underweight women drank less alcohol over a 4week-period than normal-weight females (Table 2). No significant difference concerning alcohol consumption could be found between overweight and normal-weight females (Table 3). Obese women were also found to drink
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The Relation of Weight to Women’s Health TABLE 1 Descriptive Information on Included Women N for each weight group (underweight, normal weight, overweight, N Percentage and obese) (total) (%) SES Age (years) 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59 Total
19 12 22 19 22 21 7 7 129
76 48 88 76 88 84 28 28 516
14.7 9.3 17.1 14.7 17.1 16.3 5.4 5.4 100.0
3 4 5 6 7 8 9 10 11 12 13 14 Total
N for each weight group (underweight, normal weight, overweight, N Percentage and obese) (total) (%) 2 7 10 14 15 17 16 14 14 10 3 7 129
8 28 40 56 60 68 64 56 56 40 12 28 516
1.6 5.4 7.8 10.9 11.6 13.2 12.4 10.9 10.9 7.8 2.3 5.4 100.0
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. N = number of women; SES = socioeconomic status. Analyses were calculated with females matched according to age and socioeconomic status (N = 516). The women represented in this study were included four times respectively: 129 underweight, 129 normal-weight, 129 overweight, and 129 obese females.
less alcohol over a 4-week-period than normal-weight females (Table 4). No significant differences were found among the weight groups in their smoking and eating behavior, or in physical exercise. Results of conditional logistic regression analyses also revealed no significant difference regarding health behavior between overweight and normal-weight females (Table 3).
Differences in Health and Medical Treatments Among Underweight, Overweight, or Obese and Normal Weight Women The results of the conditional logistic regression analyses revealed a significant difference between underweight, overweight, and obese women compared to normal-weight women in self-reported health. The three former groups differed significantly from normal-weight women, in that they reported poorer health (Tables 2–4). Additionally, underweight and obese women sought medical care significantly more often than normal-weight women. No significant differences were found among the weight groups in impaired health, the total number of chronic conditions, or the vascular risk score (Tables 2–4). In analyzing specific chronic conditions, normal-weight women suffered from significantly less sacrospinal complaints, migraines, other chronic conditions, and pain than the other three weight groups. Moreover, they reported significantly less osteoporosis than underweight women. Significantly more obese women reported hypertension than all other weight groups (Table 5).
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TABLE 2 Results of Conditional Regression Analyses Regarding Health Behavior, Health, Medical Treatments, and Quality of Life Comparing Underweight Women (Cases) vs. Normal Weight Women (Controls) Variable Health behavior Physical exercise (total MET score)1 Number of cigarettes per day2 Alcohol consumption (number of days within 4 weeks)2 Eating behavior3 Health and medical treatments Self-reported health generally2 Impairment due to diseases1 Number of chronic conditions2 Vascular risk2 Medical treatments (number of doctor’s visits, e.g., general practitioner, specialist)2 WHO-QOL Physical health Psychological health Social relationships Environment
Cases [M (SD)]
Controls [M (SD)]
p
Odds ratio
5026.6 (4576.2)
5742.0 (6125.1)
.890
1.000
1.000–1.000
CI (95%)
5.04 (8.74)
3.67 (7.67)
.352
0.952
0.858–1.056
3.01 (5.52)
3.89 (5.29)
.048
0.906
0.821–0.999
4.64 (1.00)
4.66 (0.79)
.494
0.838
0.506–1.390
1.81 (0.86)
1.05 (0.33)
.000 21.933 4.827–99.654
2.62 (0.63)
2.94 (0.33)
.577
1.836 0.218–15.489
1.24 (1.44)
0.60 (0.96)
.391
0.756
0.400–1.432
1.73 (0.56) 1.74 (0.97)
1.83 (0.52) 1.20 (0.84)
.093 .003
0.296 2.369
0.071–1.226 1.331–4.217
.628 .411 .009 .731
0.894 1.173 0.672 1.054
0.567–1.408 0.802–1.714 0.499–0.905 0.780–1.425
17.37 16.63 16.59 16.11
(2.51) (2.34) (2.25) (2.20)
18.73 17.44 17.71 16.77
(1.60) (1.72) (2.25) (1.81)
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. M = mean, SD = standard deviation, p = probability of test statistics, CI (95%) = confidence interval. All variables were analyzed in one model to control for possible confounding effects. The significant p-values are shown in bold. 1 A higher score means better results. 2 A higher score means worse results. 3 A higher score means higher animal fat intake/more meat consumption. Analyses were calculated with females matched according to age and socioeconomic status (N = 129 underweight and 129 normal-weight women). Possible range of the scores of each variable: Physical exercise: ≥0; number of cigarettes per day: ≥0; alcohol consumption 0–28; eating behavior: 1–6; self-reported health: 1–5; impairment due to diseases: 1–3; number of chronic conditions: 0–18; vascular risk: 0–4; medical treatments: 0–8; scores of each WHOQOL variable: 4–20.
Differences in Quality of Life Among Underweight, Overweight, or Obese and Normal Weight Women The conditional logistic regression analyses also revealed significant differences in QOL among the weight groups. Normal-weight women reported the best QOL and had significantly better QOL than obese women in the domain
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TABLE 3 Results of Conditional Regression Analyses Regarding Health Behavior, Health, Medical Treatments, and Quality of Life Comparing Overweight Women (Cases) vs. Normal Weight Females (Controls) Variable Health behavior Physical exercise (total MET score)1 Number of cigarettes per day2 Alcohol consumption (number of days within 4 weeks)2 Eating behavior3 Health and medical treatments Self-reported health generally2 Impairment due to diseases1 Number of chronic conditions2 Vascular risk2 Medical treatments (number of doctor’s visits, e.g. general practitioner, specialist)2 WHO-QOL Physical health Psychological health Social relationships Environment
Odds ratio
Cases [M (SD)]
Controls [M (SD)]
p
CI (95%)
6,519.2 (6,590.5)
5,742.0 (6,125.1)
.147
1.000
1.000–1.000
4.43 (8.14)
3.67 (7.67)
.544
1.022
0.952–1.097
3.44 (5.07)
3.89 (5.29)
.230
0.937
0.844–1.042
4.83 (0.72)
4.66 (0.79)
.946
0.985
0.636–1.526
1.77 (0.92)
1.05 (0.33)
.000 57.497 8.791–376.050
2.71 (0.53)
2.94 (0.33)
.342
2.572
0.367–18.042
1.23 (1.62)
0.60 (0.96)
.175
0.662
0.364–1.202
1.94 (0.65) 1.75 (1.47)
1.83 (0.52) 1.20 (0.84)
.482 .948
1.377 1.014
0.565–3.358 0.667–1.542
.623 .563 .037 .904
1.097 0.919 1.272 1.016
0.757–1.590 0.689–1.224 1.015–1.596 0.785–1.315
17.46 16.44 17.11 16.17
(2.55) (2.32) (2.35) (2.09)
18.73 17.44 17.71 16.77
(1.60) (1.72) (2.25) (1.81)
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. M = mean, SD = standard deviation, p = probability of test statistics, CI (95%) = confidence interval. All variables were analyzed in one model to control for possible confounding effects. The significant p-values are shown in bold. 1 A higher score means better results. 2 A higher score means worse results. 3 A higher score means higher animal fat intake/more meat consumption. Analyses were calculated with females matched according to age and socioeconomic status (N = 129 overweight and 129 normal-weight women). Possible range of the scores of each variable: Physical exercise: ≥0; number of cigarettes per day: ≥0; alcohol consumption 0–28; eating behavior: 1–6; self-reported health: 1–5; impairment due to diseases: 1–3; number of chronic conditions: 0–18; vascular risk: 0–4; medical treatments: 0–8; scores of each WHOQOL variable: 4–20.
of “psychological health”. Underweight and overweight women reported significantly worse QOL in “social relationships” than normal-weight women. No significant differences were found by weight category in the domains “physical health” and “environment” (Table 2–4).
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TABLE 4 Results of Conditional Regression Analyses Regarding Health Behavior, Health, Medical Treatments, and Quality of Life Comparing Obese Women (Cases) vs. Normal Weight Women (Controls) Variable Health behavior Physical exercise (total MET score)1 Number of cigarettes per day2 Alcohol consumption (number of days within 4 weeks)2 Eating behavior3 Health and medical treatments Self-reported health generally2 Impairment due to diseases1 Number of chronic conditions2 Vascular risk2 Medical treatments (number of doctor’s visits, e.g., general practitioner, specialist)2 WHO-QOL Physical health Psychological health Social relationships Environment
Cases [M (SD)]
Controls [M (SD)]
5,706.8 (7,115.0)
5,742.0 (6,125.1)
p
Odds ratio
CI (95%)
.065 1.000
1.000–1.000
3.17 (5.88)
3.67 (7.67)
.803 0.988
0.900–1.085
1.64 (2.97)
3.89 (5.29)
.005 0.816
0.708–0.941
5.01 (0.82)
4.66 (0.79)
.060 1.845
0.976–3.491
1.84 (0.91)
1.05 (0.33)
.002 7.478
2.138–26.153
2.64 (0.67)
2.94 (0.33)
.632 0.592
0.069–5.070
1.43 (1.61)
0.60 (0.96)
.407 0.800
0.471–1.357
2.09 (0.84) 1.74 (1.07)
1.83 (0.52) 1.20 (0.84)
.495 1.362 .019 1.894
0.561–3.305 1.111–3.228
.356 .026 .111 .125
0.833–1.662 0.462–0.953 0.618–1.051 0.938–1.682
16.91 15.89 16.92 16.24
(3.08) (2.27) (2.39) (2.05)
18.73 17.44 17.71 16.77
(1.60) (1.72) (2.25) (1.81)
1.177 0.664 0.806 1.256
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. M = mean, SD = standard deviation, p = probability of test statistics, CI (95%) = confidence interval. All variables were analyzed in one model to control for possible confounding effects. The significant p-values are shown in bold. 1 A higher score means better results. 2 A higher score means worse results. 3 A higher score means higher animal fat intake/more meat consumption. Analyses were calculated with females matched according to age and socioeconomic status (N = 129 obese and 129 normal-weight women). Possible range of the scores of each variable: Physical exercise: ≥0; number of cigarettes per day: ≥0; alcohol consumption 0–28; eating behavior: 1–6; self-reported health: 1–5; impairment due to diseases: 1–3; number of chronic conditions: 0–18; vascular risk: 0–4; medical treatments: 0–8; scores of each WHOQOL variable: 4–20.
DISCUSSION Our results showed that normal weight women were healthiest compared to underweight, overweight, and obese women. Normal-weight women reported significantly better health generally and needed less medical
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TABLE 5 Unadjusted Differences in Frequency of Various Chronic Conditions Among the Weight Groups (Underweight, Normal Weight, Overweight, or Obesity) Chronic condition Asthma∗ Allergies∗ Diabetes∗ Cataract∗ Tinnitus∗ Hypertension∗ Cardiac infarction∗ Apoplectic stroke∗ Bronchitis∗ Arthritis∗ Sacrospinal complaints∗ Osteoporosis∗ Urinary incontinency∗ Gastric or intestinal ulcer∗ Cancer∗ Migraine∗ Mental illness (anxiety disorder or depression)∗ Other chronic condition∗ Serious pain
Underweight Normal (%) weight (%)
Overweight (%)
Obese (%)
p (χ 2 )
1.6 24.0 3.1 0.8 3.1 0.8 0.0 1.6 3.9 5.4 20.9 6.2 2.3 4.7 0.8 20.2 8.5
5.4 20.9 0.0 0.0 0.8 4.7 0.0 0.8 1.6 0.8 10.1 0.8 1.6 2.3 0.0 7.8 3.1
5.4 20.9 1.6 0.0 5.4 9.3 0.8 0.8 3.1 6.2 24.0 0.0 3.1 3.1 1.6 20.9 8.5
5.4 17.8 3.9 0.8 3.1 27.1 0.0 0.8 4.7 4.7 24.0 1.6 2.3 4.7 2.3 21.7 9.3
.332 .683 .140 .571 .200
The Relation of Weight to Women’s Health: A Matched Sample Study from Austria NATHALIE T. BURKERT, Mag, ÉVA RÁSKY, Dr, FRANZISKA GROßSCHÄDL, BSc, MSc, Dr, JOHANNA MUCKENHUBER, MMag, and WOLFGANG FREIDL, Dr Institute of Social Medicine and Epidemiology, Medical University Graz, Graz, Austria
While being underweight, overweight, or obese has been associated with higher rates of morbidity and mortality, such relations have not been studied in Austrian women. Therefore, the aim of this study was to analyze differences in health, health behaviors, and quality of life among women of various weight status categories, using data from the Austrian Health Interview (AT-HIS) 2006/07. First, women between 20 and 60 years of age, from four different weight status groups (underweight, normal weight, overweight, and obese) were matched case to case on age and socioeconomic status. After matching, the total number of women included in the analyses was 516 ( N = 129 per). Differences in health status among women in different weight status categories were calculated using multiple conditional logistic regression analyses. Compared to females in the other three groups, women with normal weight had the best state of health: they had better self-reported health, suffered from fewer chronic conditions (e.g., sacrospinal complaints or migraines), and needed medical treatment less often. Moreover, they had better self-reported quality of life. In contrast, women who were underweight or obese showed worse health than women of normal weight. Appropriate health programs for weight risk groups are needed. KEYWORDS weight status, BMI, health-related behavior, health, quality of life
Received July 26, 2013; revised February 26, 2014; accepted March 10, 2014. Address correspondence to Nathalie T. Burkert, Mag, Institute of Social Medicine and Epidemiology, Medical University Graz, Universitaetsstrasse 6/I, Graz A-8010, Austria. E-mail: [email protected]
134
The Relation of Weight to Women’s Health
135
INTRODUCTION In most countries, a double burden exists related to weight—while the prevalence of overweight and obesity is rising, the prevalence of underweight is still high. An inverse relationship between educational level and body weight has been established (Ali and Lindström 2006; Großschädl, Haditsch, and Stronegger 2012; Kilicarslan et al. 2006; Roskam et al. 2010). The risk of obesity also increases with lower income (Amarasinghe et al. 2009) and is inversely associated with socioeconomic status (SES) (Burkert et al. 2012a; WHO 1998), even after adjusting for age (Brennan et al. 2009; Großschädl and Stronegger 2013). Results of the 2002/03 World Health Survey showed that in most urbanized countries, women with greater educational attainment had a lower body mass index (BMI) (Fleischer, Diez Roux, and Hubbard 2012). Additionally, BMI differed by race/ethnicity (Mack et al. 2004). Both a low BMI (underweight) as well as a high BMI (overweight and obesity) have been associated with poorer health (Franco et al. 2012; Ha do et al. 2011; Hu 2003; Khan and Kraemer 2009). Obesity has also been associated with greater multi-morbidity and a higher prevalence of chronic conditions, including hypertension, diabetes mellitus, and cardiovascular diseases (CVD) (Barnes 2011; Booth, Prevost, and Gulliford 2013; Burkert et al. 2013; Hu 2003; WHO 2012). In contrast, underweight has been related to bradycardia, hypotension, hypothermia, and osteopenia (Lemberg 1999). Moreover, women who were underweight, overweight, or obese have self-reported poorer health than women with normal weight (Ali et al. 2006). Especially for CVD, a J-shaped relationship between BMI and CVD-specific mortality has been found (Berrington de Gonzalez et al. 2010; Dudina et al. 2011), and frailty has been related to both weight loss and heart disease (Von Haehling et al. 2013). Additionally, all-cause mortality was significantly increased in underweight and obese persons (Bessonova et al. 2011) and lowest in persons with a normal BMI between 20.0 and 24.9 kg/m2 (Berrington de Gonzalez et al. 2010). Extreme body weights were also associated with more hospital stays compared to individuals with normal weight (Wulff and Wild 2011). Moreover, quality of life (QOL) has been associated with body weight, although the effect was appeared to be modified by age (Branca, Nikogosian, and Lobstein 2007; Brennan et al. 2009; Cash et al. 2011; Gallon and Wender 2012; Garner et al. 2012; Ha do et al. 2011; Khan and Kraemer 2009; Sirtori et al. 2012). Underweight in women was associated with higher QOL at younger ages but was related to lower QOL at older ages (Garner et al. 2012). Nevertheless, compared to normal-weight women the mental health of underweight women was impaired, even after controlling for demographic characteristics and lifestyle factors (Mond et al. 2011). The highest QOL score has been observed among women with a BMI of 24.5 kg/m2 (Søltoft, Hammer, and Kragh 2009).
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However, not only body weight, but also lifestyle factors had an influence on health (Bauer et al. 2009). Lifestyle factors, which have been associated with health risk, include tobacco smoking, alcohol consumption, inadequate nutrition, and physical inactivity (Branca, Nikogosian, and Lobstein 2007). All of these risk factors were more prevalent in women who were overweight/obese (Ali et al. 2006). The health risk of alcohol consumption is more complex. While moderate alcohol drinking has been related to a lower mortality rate (Adler and Newman 2002), both abstinence and excessive alcohol consumption are detrimental to health (Mackenbach 2006). Pack-years of smoking, never drinking or excessive alcohol intake, as well as physical inactivity have been associated with increased mortality. Moreover, the combination of these factors (smoking, physical inactivity, never drinking or excessive alcohol intake) with a BMI outside the normal range has been associated with an increased risk of mortality by nearly 60% (Iversen et al. 2010). In conclusion, extremes of body weight have been associated with poorer health. To our knowledge no prior study in Austria has compared the health relations of underweight, normal weight, overweight, and obesity to women’s health, health behavior, and QOL. Therefore, the aim of this study was to analyze differences in terms of health-related behavior, health, and QOL of women with different BMIs, matched according to their age and socioeconomic status.
MATERIAL AND METHODS Study Population The sample for this study was taken from the Austrian Health Interview Survey (AT-HIS), which was conducted between 2006 and 2007 (Klimont, Kytir, and Leitner 2007). The AT-HIS is a standardized survey conducted at regular intervals in Austria (currently every 8 years). The AT-HIS is part of the European Health Interview Survey (E-HIS; http://www.euhsid.org), an important survey of high quality. The participants included a representative sample of the Austrian population. The reference population for the survey included all persons who were listed in the register of residence of Austria who were aged 15 years or older. To get a representative sample, the respondents were stratified according to Austria’s different geographic regions, and the sampling was weighted according to the number of the inhabitants in the specific regions. The interviews were conducted faceto-face by persons engaged by the Austrian Statistic Agency. To ensure that all interviews were conducted in the same way, interviewers underwent 1 day of training and were given guidelines in conducting the survey. To ensure interviewer consistency, time measurement, non-response analysis, and analysis of erroneous dialogs were performed. Additionally, the work of the interviewers was overseen by field supervisors.
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Overall, 15,474 participants aged 15 years and older were interviewed through computer-assisted personal interviews (CAPI; 54.7% female). All participants were first contacted and informed about the survey by telephone. If they agreed to take part, an appointment for the CAPI was arranged. No minors or children and only those respondents who could provide information personally were included in the study. Respondents who did not speak the German language, who could not be reached after three attempts to contact them, or who were in a hospital at the time of the interview were excluded. The response rate of the AT-HIS was 63.1%. The study was carried out in compliance with the declaration of Helsinki, and the ethics committee of the Medical University of Graz approved this study protocol (EK-number: 24-288 ex 11/12). Verbal informed consent was obtained from all participants, witnessed and formally recorded before the interview. Because weight has a different influence on health in men and women (Hemmelmann et al. 2010; Hüsler et al. 2010; Kuczmarski and Flegal 2000; Nysom et al. 2001), we restricted our analyzed sample to women. Moreover, because the relation of weight to health in adolescents is different, and percentile curves are used to define extremes of body weight at these younger ages (De Onis et al. 2007), we only analyzed data from adult women aged 20 years and over. Additionally, we only analyzed data from adults who were younger than 60 years because weight increases in both men and women with age (Micozzi and Harris 1990), and the relation of BMI to disease and mortality risk differs in the elderly (Dorner and Rieder 2010; Volkert 2006). To conclude, the present analyses were carried out for women aged 20 through 59 years, stratified by their weight status. The classification for underweight, normal weight, overweight, and obesity were made according to the World Health Organization (WHO 2000) [underweight (BMI < 18.5 kg/m2 ), normal weight (BMI ≥ 18.5 kg/m2 and 11).
Differences in Health Behavior Among Underweight, Overweight, or Obese and Normal-Weight Women Our analyses showed that underweight women drank less alcohol over a 4week-period than normal-weight females (Table 2). No significant difference concerning alcohol consumption could be found between overweight and normal-weight females (Table 3). Obese women were also found to drink
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The Relation of Weight to Women’s Health TABLE 1 Descriptive Information on Included Women N for each weight group (underweight, normal weight, overweight, N Percentage and obese) (total) (%) SES Age (years) 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59 Total
19 12 22 19 22 21 7 7 129
76 48 88 76 88 84 28 28 516
14.7 9.3 17.1 14.7 17.1 16.3 5.4 5.4 100.0
3 4 5 6 7 8 9 10 11 12 13 14 Total
N for each weight group (underweight, normal weight, overweight, N Percentage and obese) (total) (%) 2 7 10 14 15 17 16 14 14 10 3 7 129
8 28 40 56 60 68 64 56 56 40 12 28 516
1.6 5.4 7.8 10.9 11.6 13.2 12.4 10.9 10.9 7.8 2.3 5.4 100.0
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. N = number of women; SES = socioeconomic status. Analyses were calculated with females matched according to age and socioeconomic status (N = 516). The women represented in this study were included four times respectively: 129 underweight, 129 normal-weight, 129 overweight, and 129 obese females.
less alcohol over a 4-week-period than normal-weight females (Table 4). No significant differences were found among the weight groups in their smoking and eating behavior, or in physical exercise. Results of conditional logistic regression analyses also revealed no significant difference regarding health behavior between overweight and normal-weight females (Table 3).
Differences in Health and Medical Treatments Among Underweight, Overweight, or Obese and Normal Weight Women The results of the conditional logistic regression analyses revealed a significant difference between underweight, overweight, and obese women compared to normal-weight women in self-reported health. The three former groups differed significantly from normal-weight women, in that they reported poorer health (Tables 2–4). Additionally, underweight and obese women sought medical care significantly more often than normal-weight women. No significant differences were found among the weight groups in impaired health, the total number of chronic conditions, or the vascular risk score (Tables 2–4). In analyzing specific chronic conditions, normal-weight women suffered from significantly less sacrospinal complaints, migraines, other chronic conditions, and pain than the other three weight groups. Moreover, they reported significantly less osteoporosis than underweight women. Significantly more obese women reported hypertension than all other weight groups (Table 5).
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TABLE 2 Results of Conditional Regression Analyses Regarding Health Behavior, Health, Medical Treatments, and Quality of Life Comparing Underweight Women (Cases) vs. Normal Weight Women (Controls) Variable Health behavior Physical exercise (total MET score)1 Number of cigarettes per day2 Alcohol consumption (number of days within 4 weeks)2 Eating behavior3 Health and medical treatments Self-reported health generally2 Impairment due to diseases1 Number of chronic conditions2 Vascular risk2 Medical treatments (number of doctor’s visits, e.g., general practitioner, specialist)2 WHO-QOL Physical health Psychological health Social relationships Environment
Cases [M (SD)]
Controls [M (SD)]
p
Odds ratio
5026.6 (4576.2)
5742.0 (6125.1)
.890
1.000
1.000–1.000
CI (95%)
5.04 (8.74)
3.67 (7.67)
.352
0.952
0.858–1.056
3.01 (5.52)
3.89 (5.29)
.048
0.906
0.821–0.999
4.64 (1.00)
4.66 (0.79)
.494
0.838
0.506–1.390
1.81 (0.86)
1.05 (0.33)
.000 21.933 4.827–99.654
2.62 (0.63)
2.94 (0.33)
.577
1.836 0.218–15.489
1.24 (1.44)
0.60 (0.96)
.391
0.756
0.400–1.432
1.73 (0.56) 1.74 (0.97)
1.83 (0.52) 1.20 (0.84)
.093 .003
0.296 2.369
0.071–1.226 1.331–4.217
.628 .411 .009 .731
0.894 1.173 0.672 1.054
0.567–1.408 0.802–1.714 0.499–0.905 0.780–1.425
17.37 16.63 16.59 16.11
(2.51) (2.34) (2.25) (2.20)
18.73 17.44 17.71 16.77
(1.60) (1.72) (2.25) (1.81)
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. M = mean, SD = standard deviation, p = probability of test statistics, CI (95%) = confidence interval. All variables were analyzed in one model to control for possible confounding effects. The significant p-values are shown in bold. 1 A higher score means better results. 2 A higher score means worse results. 3 A higher score means higher animal fat intake/more meat consumption. Analyses were calculated with females matched according to age and socioeconomic status (N = 129 underweight and 129 normal-weight women). Possible range of the scores of each variable: Physical exercise: ≥0; number of cigarettes per day: ≥0; alcohol consumption 0–28; eating behavior: 1–6; self-reported health: 1–5; impairment due to diseases: 1–3; number of chronic conditions: 0–18; vascular risk: 0–4; medical treatments: 0–8; scores of each WHOQOL variable: 4–20.
Differences in Quality of Life Among Underweight, Overweight, or Obese and Normal Weight Women The conditional logistic regression analyses also revealed significant differences in QOL among the weight groups. Normal-weight women reported the best QOL and had significantly better QOL than obese women in the domain
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TABLE 3 Results of Conditional Regression Analyses Regarding Health Behavior, Health, Medical Treatments, and Quality of Life Comparing Overweight Women (Cases) vs. Normal Weight Females (Controls) Variable Health behavior Physical exercise (total MET score)1 Number of cigarettes per day2 Alcohol consumption (number of days within 4 weeks)2 Eating behavior3 Health and medical treatments Self-reported health generally2 Impairment due to diseases1 Number of chronic conditions2 Vascular risk2 Medical treatments (number of doctor’s visits, e.g. general practitioner, specialist)2 WHO-QOL Physical health Psychological health Social relationships Environment
Odds ratio
Cases [M (SD)]
Controls [M (SD)]
p
CI (95%)
6,519.2 (6,590.5)
5,742.0 (6,125.1)
.147
1.000
1.000–1.000
4.43 (8.14)
3.67 (7.67)
.544
1.022
0.952–1.097
3.44 (5.07)
3.89 (5.29)
.230
0.937
0.844–1.042
4.83 (0.72)
4.66 (0.79)
.946
0.985
0.636–1.526
1.77 (0.92)
1.05 (0.33)
.000 57.497 8.791–376.050
2.71 (0.53)
2.94 (0.33)
.342
2.572
0.367–18.042
1.23 (1.62)
0.60 (0.96)
.175
0.662
0.364–1.202
1.94 (0.65) 1.75 (1.47)
1.83 (0.52) 1.20 (0.84)
.482 .948
1.377 1.014
0.565–3.358 0.667–1.542
.623 .563 .037 .904
1.097 0.919 1.272 1.016
0.757–1.590 0.689–1.224 1.015–1.596 0.785–1.315
17.46 16.44 17.11 16.17
(2.55) (2.32) (2.35) (2.09)
18.73 17.44 17.71 16.77
(1.60) (1.72) (2.25) (1.81)
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. M = mean, SD = standard deviation, p = probability of test statistics, CI (95%) = confidence interval. All variables were analyzed in one model to control for possible confounding effects. The significant p-values are shown in bold. 1 A higher score means better results. 2 A higher score means worse results. 3 A higher score means higher animal fat intake/more meat consumption. Analyses were calculated with females matched according to age and socioeconomic status (N = 129 overweight and 129 normal-weight women). Possible range of the scores of each variable: Physical exercise: ≥0; number of cigarettes per day: ≥0; alcohol consumption 0–28; eating behavior: 1–6; self-reported health: 1–5; impairment due to diseases: 1–3; number of chronic conditions: 0–18; vascular risk: 0–4; medical treatments: 0–8; scores of each WHOQOL variable: 4–20.
of “psychological health”. Underweight and overweight women reported significantly worse QOL in “social relationships” than normal-weight women. No significant differences were found by weight category in the domains “physical health” and “environment” (Table 2–4).
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TABLE 4 Results of Conditional Regression Analyses Regarding Health Behavior, Health, Medical Treatments, and Quality of Life Comparing Obese Women (Cases) vs. Normal Weight Women (Controls) Variable Health behavior Physical exercise (total MET score)1 Number of cigarettes per day2 Alcohol consumption (number of days within 4 weeks)2 Eating behavior3 Health and medical treatments Self-reported health generally2 Impairment due to diseases1 Number of chronic conditions2 Vascular risk2 Medical treatments (number of doctor’s visits, e.g., general practitioner, specialist)2 WHO-QOL Physical health Psychological health Social relationships Environment
Cases [M (SD)]
Controls [M (SD)]
5,706.8 (7,115.0)
5,742.0 (6,125.1)
p
Odds ratio
CI (95%)
.065 1.000
1.000–1.000
3.17 (5.88)
3.67 (7.67)
.803 0.988
0.900–1.085
1.64 (2.97)
3.89 (5.29)
.005 0.816
0.708–0.941
5.01 (0.82)
4.66 (0.79)
.060 1.845
0.976–3.491
1.84 (0.91)
1.05 (0.33)
.002 7.478
2.138–26.153
2.64 (0.67)
2.94 (0.33)
.632 0.592
0.069–5.070
1.43 (1.61)
0.60 (0.96)
.407 0.800
0.471–1.357
2.09 (0.84) 1.74 (1.07)
1.83 (0.52) 1.20 (0.84)
.495 1.362 .019 1.894
0.561–3.305 1.111–3.228
.356 .026 .111 .125
0.833–1.662 0.462–0.953 0.618–1.051 0.938–1.682
16.91 15.89 16.92 16.24
(3.08) (2.27) (2.39) (2.05)
18.73 17.44 17.71 16.77
(1.60) (1.72) (2.25) (1.81)
1.177 0.664 0.806 1.256
Note: Data source: Austrian Health Interview Survey (AT-HIS) 2006/07. M = mean, SD = standard deviation, p = probability of test statistics, CI (95%) = confidence interval. All variables were analyzed in one model to control for possible confounding effects. The significant p-values are shown in bold. 1 A higher score means better results. 2 A higher score means worse results. 3 A higher score means higher animal fat intake/more meat consumption. Analyses were calculated with females matched according to age and socioeconomic status (N = 129 obese and 129 normal-weight women). Possible range of the scores of each variable: Physical exercise: ≥0; number of cigarettes per day: ≥0; alcohol consumption 0–28; eating behavior: 1–6; self-reported health: 1–5; impairment due to diseases: 1–3; number of chronic conditions: 0–18; vascular risk: 0–4; medical treatments: 0–8; scores of each WHOQOL variable: 4–20.
DISCUSSION Our results showed that normal weight women were healthiest compared to underweight, overweight, and obese women. Normal-weight women reported significantly better health generally and needed less medical
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TABLE 5 Unadjusted Differences in Frequency of Various Chronic Conditions Among the Weight Groups (Underweight, Normal Weight, Overweight, or Obesity) Chronic condition Asthma∗ Allergies∗ Diabetes∗ Cataract∗ Tinnitus∗ Hypertension∗ Cardiac infarction∗ Apoplectic stroke∗ Bronchitis∗ Arthritis∗ Sacrospinal complaints∗ Osteoporosis∗ Urinary incontinency∗ Gastric or intestinal ulcer∗ Cancer∗ Migraine∗ Mental illness (anxiety disorder or depression)∗ Other chronic condition∗ Serious pain
Underweight Normal (%) weight (%)
Overweight (%)
Obese (%)
p (χ 2 )
1.6 24.0 3.1 0.8 3.1 0.8 0.0 1.6 3.9 5.4 20.9 6.2 2.3 4.7 0.8 20.2 8.5
5.4 20.9 0.0 0.0 0.8 4.7 0.0 0.8 1.6 0.8 10.1 0.8 1.6 2.3 0.0 7.8 3.1
5.4 20.9 1.6 0.0 5.4 9.3 0.8 0.8 3.1 6.2 24.0 0.0 3.1 3.1 1.6 20.9 8.5
5.4 17.8 3.9 0.8 3.1 27.1 0.0 0.8 4.7 4.7 24.0 1.6 2.3 4.7 2.3 21.7 9.3
.332 .683 .140 .571 .200
