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Article

Self-Report Dieters: Who Are They?

by
Laura Sares-Jäske
1,2,*,
Paul Knekt
1,
Satu Männistö
1,
Olavi Lindfors
1 and
Markku Heliövaara
1
1
Department of Public Health Solutions, National Institute for Health and Welfare, 00271 Helsinki, Finland
2
Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
*
Author to whom correspondence should be addressed.
Nutrients 2019, 11(8), 1789; https://doi.org/10.3390/nu11081789
Submission received: 31 May 2019 / Revised: 30 July 2019 / Accepted: 31 July 2019 / Published: 2 August 2019
Versions Notes

Abstract

:
Dieting attempts have become popular worldwide. Dieting, however, seems to have both positive and negative health-related consequences. So far, only a few studies have focused on the determinants of dieting in detail. This study explores the association between self-report dieting attempts and intentional weight loss (IWL) during the previous year and several demographic, lifestyle, health, and psychological factors in a cross-sectional study design using data from the representative Finnish Health 2000 Survey. The sample comprised 2147 men and 2378 women, aged 30–69. Information for potential determinants was assembled via health examinations, interviews, and questionnaires. Approximately 24% of the men and 39% of the women reported dieting attempts and 10% of the men and 15% of the women reported IWL. Dieting attempts were associated with younger age, education, BMI, formerly smoking, more favourable values in lifestyle variables, and unfavorable values in serum HDL and triglycerides, a worse sense of coherence, concerns about one’s appearance, and concerns about one’s health. Among men, diabetics and those sleeping ≤6 h a night more frequently reported dieting attempts and those with osteoarthritis reported IWL. Moreover, the gradient between BMI and dieting attempts was significantly stronger in men than in women. Men seem to attempt dieting when they have actual health-related reasons, while such reasons are not so strongly associated with dieting in women. These findings can be used for determining subpopulations with obesity and real weight-loss needs and, alternatively, subpopulations with normal weight unnecessarily attempting dieting.

1. Introduction

Obesity acts as a major burden on public health by increasing the risk of several chronic diseases, such as cardiovascular diseases, type 2 diabetes (T2D), some cancers, osteoarthritis, and depression [1]. Accordingly, dieting is used as a prevention strategy against the occurrence of such diseases and, indeed, successful and sustained weight loss benefits individuals with obesity [2,3]. Longitudinal epidemiological studies, however, have shown subsequent excess weight gain among dieters [4,5,6,7]. Moreover, dieting attempts may have other adverse consequences by inducing weight cycling, which has been suggested to be related to fluctuations in metabolic and cardiovascular risk factors (e.g., blood pressure, serum lipids, and plasma glucose) and the elevated risk of metabolic syndrome [8,9]. In general, the known health consequences of weight cycling seem to remain inconsistent [10,11].
In addition to health-related reasons, individuals attempt dieting due to appearance, sport activities, and social or cultural pressure. Overall, more than 40% of the adult population worldwide have reported dieting attempts at some point in their life [12]. In spite of such popularity, however, studies on dieting attempts and intentional weight loss (IWL) at the population level have been relatively scarce.
In the light of the high prevalence and possible contradictory consequences, it is essential to study the distribution of dieting according to relevant determinants in order to be able to identify the persons who report dieting. This knowledge could be utilized in preventing possible weight gain potentially resulting from unnecessary dieting. Moreover, information on the determinants of dieting is needed to be able to assess, without bias, whether dieting predicts the occurrence of non-communicable diseases. Previous studies have shown that the prevalence of dieting attempts or intentional weight loss (IWL) varies with sex [12,13], age [14,15,16,17,18], education [14,15,16,17,19,20], income [14,20,21], physical activity [22,23,24,25], weight [12,13], and indicators of dietary habits [24,26,27,28,29,30,31]. However, there is a need for studies that simultaneously cover socio-demographic factors, lifestyle, metabolic biomarkers, somatic diseases, and mental health factors at population level.
This is the first study that simultaneously explores a comprehensive set of factors for their associations with dieting in a nationally representative general adult population.

2. Materials and Methods

2.1. Study Population

The present study is based on the Health 2000 Survey (BRIF8901) carried out during 2000–2001 [32]. The sample, representative of the Finnish adult population, was drawn with a two-stage stratified cluster sampling design from 80 districts in mainland Finland. The sample included 8028 individuals aged 30 years and over. Of this sample, 6771 (84% of the sample) took part in a health examination. The sample used in this study comprised 4525 individuals (2147 men and 2378 women) who were 30–69 years old, not pregnant, had measured BMI information available, and had information available on dieting attempts and weight loss during the previous year.

2.2. Methods

2.2.1. Dieting Variables

Information on dieting attempts (‘Have you tried to lose weight during the last 12 months? No/Yes’) and weight loss (‘Have you lost weight during the last 12 months? No/Yes’) during the previous year was assessed using a self-administered questionnaire. An IWL variable was created by combining the two variables; participants answering ‘yes’ to both questions were recoded as having IWL. Although an additional question concerned the amount of lost weight, we included all individuals who had tried to lose weight and had lost weight as those with IWL, regardless of the amount of weight lost during the previous year (any amount from 1 kg upwards).
Data on the potential determinants of dieting was drawn from questionnaires, interviews, a health examination, and national registers.

2.2.2. Socio-Demographic Factors

Information concerning sex, age, and residential area was collected from national registers. A residential area was divided into urban town, densely populated municipality, and rural municipality. Information on education and marital status was collected with an interview. Education was categorized as a three-class variable, as follows: Low (did not graduate from upper secondary school or vocational school), intermediate (graduated from upper secondary school or vocational school), and high (graduated from university or vocational college). Marital status was divided into four categories, as follows: Married or cohabiting, divorced or separated, widowed, and single.

2.2.3. Lifestyle-Related Factors

Data for anthropometric measurements was measured at the health examination while wearing light clothing and no shoes. Height (cm) was measured with a wall-mounted stadiometer with the participant standing and with a precision rate of 0.5 cm. Weight (kg) and fat free mass (kg) were measured with an eight-polar bioimpedance device (InBody 3.0, Biospace, Seoul, South Korea). The results were recorded with an accuracy of 0.1 kg. The BMI was calculated as weight (kg) divided by the square of the height (m2). Normal weight was defined as BMI < 25 kg/m2, overweight as BMI 25–29.9 kg/m2, and obesity as BMI ≥ 30 kg/m2 [33]. As the sample included only 29 individuals who were underweight (BMI < 18.5 kg/m2), they were combined with those who had normal weight. A fat free mass index (FFMI) was calculated as fat free mass (kg) divided by the square of the height (m2). Leisure-time physical activity was measured via a self-administered questionnaire and divided into three categories, as follows: Low physical activity (those not physically active), moderate physical activity (those regularly engaging in light physical activity like walking or cycling), and regular physical training (those reporting exercising for three hours or more per week or training for competitive sports).
Data on sitting time was derived from a self-administered questionnaire. The participants were asked how many hours they sit during an ordinary weekday and weekend day. Sitting time on a weekday was multiplied by five and sitting time on a weekend day was multiplied by two. The products were summed together and divided by seven. The average daily sitting time was further divided into sex-specific tertiles.
Information on smoking was collected by interviews [32]. Individuals were categorized into never smokers, former smokers, and current smokers.
The habitual diet was measured with a self-administered food frequency questionnaire (FFQ) assessing food intake over the last 12 months [34,35]. The National Food Composition Database (Fineli®) and in-house software (Finessi) [36] were used to calculate the average daily intake of food groups, energy, and nutrients. The Alternate Healthy Eating Index (AHEI) [37] was used as a measure of the quality of the diet. The AHEI used in this study was composed to imitate the original AHEI as closely as possible, while paying attention to the special characteristics of the Finnish dietary culture [38]. Information on the daily consumption of certain sugary products was collected through a questionnaire. The questions concerned the consumption of (1) juices, soft drinks, and hot chocolate, (2) toffee, licorice, and dried fruit (e.g., raisins), (3) sweets, hard pastilles, and candy without xylitol, and (4) chocolate and filled biscuits. Each question included the response options ‘3 times a day or more often’, ‘Once or twice a day’, ‘2 to 5 times a week’, ‘More rarely’, and ‘Never’. The alternatives ‘3 times a day or more often’ and ‘Once or twice a day’ for any of the products were coded as daily consumption.
Information about the average sleep duration during 24 h was asked on a questionnaire. Sleep duration was categorized as ‘≤6 h’, ‘7–8 h’, and ‘≥9 h’.
Alcohol consumption (grams ethanol/week) was measured on a questionnaire and was divided into non-users, moderate users (1–199 g ethanol/week for males and 1–99 g ethanol/week for females) and heavy users (200 g ethanol/week or over for males and 100 g ethanol/week or over for females).

2.2.4. Somatic Health

Serum triglycerides (automated enzymatic method, Olympus system reagent, Germany), serum HDL cholesterol (enzymatic method, Roche Diagnostics, Mannheim, Germany), and serum fasting glucose (hexokinase, Olympus System Reagent, Germany) concentration were determined from frozen (−70 °C) serum samples taken during the health examination. We used the threshold values of the International Diabetes Federation (IDF) for the metabolic syndrome [39] in order to categorize these variables, as follows: For serum triglycerides (mmol/L) <1.7 and ≥1.7, for serum HDL cholesterol (mmol/L) ≥1.03 in men and ≥1.29 in women and <1.03 in men and <1.29 in women, and for fasting glucose (mmol/L) <5.6 and ≥5.6.
Blood pressure was measured at the health examination with a standard mercury manometer (Mercuro 300, Speidel & Keller, Jungingen, Germany) twice, with a two-minute interval, and the mean of the two measurements was calculated. The information on the use of antihypertensive medication was drawn from the interview. Elevated blood pressure was determined according to the IDF’s definition [39], as follows: Systolic pressure ≥130 mmHg or diastolic pressure ≥85 mmHg, or the use of antihypertensive medication.
Information for the T2D (ICD-10, E11) variable was assembled from questionnaires, an interview, the health examination, and a nationwide register of patients receiving diabetes medication reimbursement that is kept by the Social Insurance Institution. The registers were linked to the study population by the unique social security numbers of each Finnish citizen. Osteoarthritis in the knee and hip joints was diagnosed by trained physicians (who worked according to written instructions and applied preset criteria) at the health examination on the basis of standardized physical status, symptoms, and medical history [32,40].

2.2.5. Mental Health

Depressive and anxiety disorders were diagnosed using the German Composite International Diagnostic Interview (M-CIDI) and the DSM-IV diagnostics [41]. Concerns about one’s appearance and concerns about one’s health were measured by two items on the self-administered Beck Depression Inventory (BDI) [42]. Sense of coherence (SOC, i.e., a disposition to consider life as comprehensible, manageable, and meaningful) was assessed using the self-administered multidimensional coping inventory—the SOC-13 scale [43]. Social support received from people close to oneself was measured with a self-administered scale on a questionnaire.

2.3. Statistical Methods

The linear and logistic models were used to determine the strength of association between the potential determinants and the two outcome variables (i.e., self-report dieting attempts and previous IWL). The effect size for the independent variables was estimated as the model-adjusted mean [44] in the categories of variables in the linear model and as the relative odds in the logistic model.
Men and women were analyzed separately and combined and the potential determinants were grouped into four domains, as follows: Socio-demographic, lifestyle, somatic health, and psychiatric and psychological factors. Two models were used. Model 1 included sex and age. Model 2 (the full model) included sex (only when men and women were analyzed combined), age, education, BMI, FFMI, leisure-time physical activity, sitting time, smoking, energy intake, AHEI, daily consumption of certain sugary products, sleep duration, serum triglycerides, serum HDL cholesterol, blood pressure, T2D, osteoarthritis, SOC, concerns about one’s appearance, and concerns about one’s health. The full model was evaluated in separate domain-specific analyses and the variables were collected, excluding those which were not significant (e.g., marital status, residential area, alcohol consumption, depressive disorder, anxiety disorder, and social support received from people close to oneself) or were illogical (serum fasting glucose) in the domain-specific analyses.
In addition to BMI and FFMI, other measures of body composition (e.g., waist circumference (cm) and fat mass index (fat mass kg/m2)) were considered to be included as determinants. However, due to high correlations between them and BMI and as their associations with the dieting variables were nearly similar to those of BMI, these measures were excluded from this study and BMI was chosen to represent such obesity measures. FFMI was chosen to be included as its associations with the dieting variables differed more distinctly from corresponding associations of the other body composition measures.
The possible effect modification of sex or BMI was studied by including an interaction term in the model, between the respective variable and the potential determinants.
Due to the numerous analyses in this study, we performed a Bonferroni correction, which attenuated part of the associations to be non-significant. However, when performing a Bonferroni correction, the possibility of rejecting true positive findings grows and, as the findings met our initial hypotheses, we chose to approve the found results.
All analyses were conducted using SAS 9.3 [45].

3. Results

Of the men, 24% had attempted to diet and 10% had intentionally lost weight during the previous year, whereas of the women, as expected, the corresponding numbers were higher—39% and 15% (Table 1). The mean age of the study population was 47.9 years and approximately one third of them were highly educated. The mean BMI was 26.8 kg/m2. Roughly one-fifth participated in regular vigorous training and one-third were current smokers. In all, 27% of the men reported daily consumption of certain sugary products, while the corresponding value for the women was 19%. Of the men, 11% were concerned about their appearance and 28% about their health and of the women, the values were 22% and 33%, respectively.

3.1. Dieting Attempts

3.1.1. Sociodemographic Factors and Dieting Attempts

Dieting attempts and age had a statistically significant inverse gradient, with relative odds of 0.63 (95% CI 0.41–0.99) in men and 0.37 (95% CI 0.25–0.55) in women between individuals 60–69 and 30–39 years old (p-value for sex interaction = 0.02) (Table 2). Higher education was related to dieting attempts, whereas marital status, the number of children, and residential area did not show any association.

3.1.2. Lifestyle and Dieting Attempts

In line with the previous findings, dieting attempts were strongly dependent on BMI, especially in men (p-value for sex interaction <0.001) (Table 2). The relative odds of dieting attempts between individuals with obesity and individuals with normal weight in the multivariate model were 9.54 (95% CI 5.33–17.1) in men and 2.81 (95% CI 1.83–4.31) in women. Moreover, the relative odds of dieting attempts were elevated in the three middle quintiles of the FFMI, compared to the lowest quintile. Dieting attempts were also frequent in individuals who were physically more active during their leisure time (for regular vigorous training vs. low activity: OR = 1.65, 95% CI 1.29–2.09) and in individuals sitting more during the day. Former smokers were more commonly dieters than those who have never smoked or current smokers. The AHEI showed a statistically significant positive gradient with dieting attempts, whereas energy intake and the daily consumption of certain sugary products showed an inverse association. Short sleep duration was associated with dieting attempts in men. No association between dieting attempts and alcohol consumption was found.
BMI and smoking had a suggestive interaction (p-value for interaction = 0.12), the relative odds of dieting attempts for ex-smokers with obesity compared to never-smokers with obesity being 1.85 (95% CI 1.27–2.70), whereas no similar association was seen in the other BMI groups (Table S1). Individuals within the highest energy intake quintile had lower odds of having made dieting attempts compared to those in the lowest intake quintile among those with normal weight and those with overweight (OR = 0.43, 95% CI 0.26–0.69 and OR = 0.56, 95% CI 0.39–0.79, respectively), whereas in those with obesity, no such association was observed (p-value for interaction = 0.02). Moreover, the daily consumption of certain sugary products had a statistically significant interaction with BMI (p = 0.002). While individuals with normal weight or obesity did not show significant differences between consumption groups, those who had overweight and consuming sugary products daily had lowered odds of dieting attempts compared to those who hadoverweight and not consuming sugary products daily (OR 0.53, 95% CI 0.40–0.72).

3.1.3. Somatic Health and Dieting Attempts

The study of somatic health-related factors (after age adjustment) relatively consistently showed dieting attempts to be statistically significantly more frequent in persons with symptoms of metabolic syndrome or a diagnosed disease (Table 2). After the inclusion of all variables in the multivariate model, men with T2D had significantly greater odds of making dieting attempts compared to those without T2D (OR = 2.13, 95% CI 1.20–3.78); whereas in women, having T2D showed no association with dieting attempts (p-value for sex interaction = 0.02). On the contrary, despite the lack of significant sex interaction in the multivariate model, the associations between dieting attempts and elevated serum triglycerides and lowered serum HDL remained significant, principally in women.
Generally, no significant interactions appeared between BMI and the indicators of somatic health considered in the prediction of dieting attempts (Table S1). The only exception was knee or hip osteoarthritis (p-value for BMI interaction = 0.03), which showed suggestive elevated relative odds (1.65, 95% CI 0.99–2.77) between the subjects with and without it in the group with overweight.

3.1.4. Mental Health and Dieting Attempts

Neither diagnosed depressive or anxiety disorders nor social support received from people close to oneself were significantly related to dieting attempts. In terms of SOC, however, the frequency of dieting attempts was higher with lower SOC levels (OR = 1.45, 95% CI 1.15–1.82 between the lowest and the highest quartile) (Table 2). Moreover, dieting attempts were related to concerns about one’s appearance and one’s health. Despite the lack of significant sex interactions, the relation to concerns for one’s health was pronounced in men (OR = 1.37, 95% CI 1.04–1.81).
No significant interactions appeared between BMI and psychiatric or psychological factors when predicting dieting attempts (Table S1). However, BMI and concerns about one’s appearance showed a non-significant suggestive interaction, according to which the concerns seemed to be more strongly associated with dieting attempts in individuals with normal weight or withoverweight than in individuals with obesity.

3.2. IWL

3.2.1. Sociodemographic Factors and IWL

In the multivariate model, previous IWL was statistically significantly associated with younger age with a relative odds of 0.42 (95% CI 0.29–0.62) between individuals aged 60–69 and 30–39. The association was more pronounced in women (p-value for sex interaction = 0.05) (Table 3). Higher education was related to IWL, whereas no associations appeared for any of the other sociodemographic variables considered.
In the interaction analyses of BMI and sociodemographic factors, BMI and sex showed a significant interaction (p = 0.01) (Table S1). In those with normal weight, women had nearly triple the odds of having intentionally lost weight compared to men (OR = 2.92, 95% CI 1.80–4.74), whereas in those with obesity there were no significant differences between men and women.

3.2.2. Lifestyle and IWL

A suggestive association emerged between BMI and IWL due to a strong association among men. The relative odds between men with obesity and men with normal weight was 4.44 (95% CI 2.03–9.67, p-value for sex interaction = 0.01) (Table 3). In women, no differences occurred between the pre-defined BMI groups. Moreover, IWL was unusual in individuals with the lowest FFMI values. Of the other lifestyle-related variables, moderate leisure-time physical activity, long sitting time, and smoking (both currently and formerly) were related to IWL. In addition, IWL was associated with having a higher quality of diet, lower energy intake and not consuming daily certain sugary products. Moreover, short sleep duration was associated with IWL in men.
No significant interaction appeared between BMI and the lifestyle-related factors (Table S1). However, BMI and energy intake showed a tendency for an interaction (p = 0.15). Energy intake was only significantly inversely associated with IWL in individuals with normal weight.

3.2.3. Somatic Health and IWL

IWL was associated with low serum HDL cholesterol (OR = 1.33, 95% CI 1.07–1.65 between low and normal concentration) (Table 3). In men, those having T2D or knee or hip osteoarthritis had more commonly intentionally lost weight, the relative odds being 2.16 (95% CI 1.13–4.15) for T2D and 2.27 (95% CI 1.21–4.29) for osteoarthritis. In general, no significant interaction appeared between BMI and the indicators of somatic health that were considered (Table S1). The only exception was osteoarthritis (p-value for interaction = 0.01), which showed a strong positive association in individuals who had overweight (OR = 2.74, 95% CI 1.51–4.97).

3.2.4. Mental Health and IWL

IWL was associated with none of the psychiatric or psychological factors in the additive model. There was, however, a significant interaction for concern about one’s appearance and BMI (p = 0.02) (Table S1). Individuals with normal weight and concerns about their appearance had more frequently intentionally lost weight compared to those without concerns about their appearance (OR = 1.71, 95% CI 1.07–2.72), while no differences appeared in those with obesity or with overweight.

4. Discussion

We found dieting attempts and IWL to be more common in younger age groups, particularly in women, which is in line with previous findings [14,15,16,17,18,21,46,47,48,49,50,51]. Both younger individuals and women, in particular, are affected by social pressure and the desire to be lean [52]. Dieting attempts and IWL being more frequent in those with higher education is backed up in the previous literature [14,15,17,19,20,21,29,31,47,53,54]. Education increases knowledge on the harmful consequences of obesity, which might push more highly educated individuals to try to lose weight more often. Moreover, it is possible that social pressure to be lean is more prevalent among those with higher education.
Individuals within the three middle FFMI quintiles had attempted dieting more often than those within the lowest or the highest quintiles. The lack of association between the highest and lowest quintiles derived from the presence of BMI in the multivariate model, suggesting that high FFMI in the absence of obesity is not associated with dieting. Loss of muscle mass has been linked to impaired functional capacity and mortality [55], hence the need or resources to attempt dieting may be absent in the lives of those with low FFMI values. Alternatively, it is possible that measuring fat free mass with bioimpedance may not be accurate for individuals with extreme BMI values or with abnormal hydration [56]. In the sex-specific analysis, women with the highest FFMI had intentionally lost weight over twice as often as women with the lowest FFMI. The FFMI measures the amount of fat free mass relative to the person’s height [57]. It may be that a higher FFMI is a result of intentionally losing weight and, expressly, fat mass. Alternatively, it is possible that those in the highest quintile are more often athletes and, particularly in women, feel the need to lose weight in order to stay in good shape. Surprisingly, even though women with the highest FFMI had most frequently lost weight intentionally, the same group of women did not differ from those with the lowest FFMI with regard to dieting attempts. Indeed, it seems that women with the highest FFMI did not attempt dieting any more often than women with lower values; but when they did so, they more commonly succeeded.
Our finding on the positive association between BMI and dieting attempts is in line with previous results [5,14,15,16,17,18,20,21,26,29,46,47,48,49,51,58,59,60,61,62,63,64,65]. People with obesity may have health-related reasons and other personal reasons to attempt to lose weight, but they may also have more social pressure to report dieting even though they have not necessarily dieted. Even though women within each BMI category reported dieting attempts more often than men, the difference between sexes was more pronounced at lower BMI levels, which is consistent with the previous literature [15,16,17,19,20,48]. In modern societies, women seem to have stricter social ideal weight norms and diet when they have normal weight, whereas the authors speculate that men start dieting when they actually become affected by overweight or obesity. After controlling for potential confounding factors, IWL was only related to BMI in men. Apparently, men with obesity take weight-loss efforts more seriously, while for women, a higher BMI does not make a difference to the successfulness of dieting attempts.
As far as we know, our finding on more sitting time being positively associated with dieting attempts and IWL was the first on this topic. Obesity, however, has been found to be associated with more sitting time [66].
Physical activity was positively associated with dieting attempts, which is in line with most [21,22,23,24,25,67] but not all previous results [58]. Physical activity may be a strategy to attempt to lose weight [12] or it may be that, in the vigorous physical activity category, there are more athletes who take part in competitive sports. Such athletes may diet to stay in shape and for optimal performance. Alternatively, it is also possible that those who feel pressure to report dieting (those with obesity) also feel pressure to report vigorous physical activity while not actually dieting or exercising.
Dieting attempts and IWL were more prevalent in former smokers than in those who had never smoked, especially in women and in individuals with obesity. However, even though there are some contrary findings on former smoking in men [17], some studies support these results [14,16]. Former smokers may have gained weight after quitting smoking and consequently try to lose weight [68]. Alternatively, former smokers may have made a lifestyle change that includes both quitting smoking and dieting to lose weight.
Our findings are in line with the results of previous studies regarding the inverse associations between energy intake and dieting attempts and IWL [27,29,30,31,38,69], the direct association between quality of diet (or in previous studies, the components of a healthy diet) and dieting attempts and IWL [24,26,28,31,38,69], and the inverse associations between the daily consumption of certain sugary products and dieting attempts and IWL [22,24,28,64,69]. This is presumably due to using dieting (both decreasing energy intake and altering one’s diet to be healthier) as a strategy to lose weight [12]. Dieters, moreover, have been shown to under-report their energy intake (especially their intake of sugary and fatty foods) and over-report their intake of food items considered healthy and socially desirable (e.g., vegetables), which may lead to biased results [70]. The importance of dietary habits is crucial in the development of obesity and numerous diseases. Thus, the role of a healthy diet, and not just counting calories, is essential when trying to prevent chronic diseases [71].
When looking into associations between energy intake and dieting attempts in BMI categories, significant inverse associations only emerged in those with normal weight or those who had overweight, while in those with obesity, the association remained non-existent. This is contrary to the finding by Neumark-Sztainer et al. [54], according to which a significant inverse association only emerged among those who had overweight, but not among those with normal weight. In men only, those sleeping ≤6 h a night had attempted dieting and had had IWL more often than those sleeping 7 to 8 h a night. In accordance, a Canadian study showed a short sleep duration to be associated with dieting attempts and previous weight loss [72]. A short sleep duration has also been linked to obesity and findings even suggest that it acts as an obstacle to weight loss [73]. Hence, those sleeping inadequately may attempt dieting and have IWL due to short sleep-related weight gain. However, the association remained significant even after adjusting for BMI. Thus, it is possible that some other reasons lie behind the association.
No previous studies exist on the association between serum triglycerides and dieting attempts at the population level. One study, however, demonstrated that young women with high dietary restraint had higher serum triglycerides than those with low dietary restraint [74]. In addition, high serum cholesterol has been associated with dieting attempts [18,58]. Moreover, weight cycling, in most cases following repeated dieting periods, has been found to be associated with elevated serum lipids [75]. Indeed, weight regain after weight loss may elevate levels beyond their initial value. Hence, it is possible that the positive association found in our study, primarily in women, derives from previous dieting attempts and weight regain. Alternatively, awareness of disadvantageous values may drive individuals to try to lose weight. Additionally, these possible reasons may also hold true for the inverse associations found between HDL and dieting attempts and IWL, maybe more strongly in women.
T2D was only associated with dieting attempts and IWL in men. Findings from an American study support this association, although in that study the connection was found in both sexes [58]. However, in a Canadian study, T2D was found to be unrelated to dieting attempts [23]. The association between knee or hip osteoarthritis and dieting attempts and IWL at the population level has been, prior to the present study, an unexamined field, although weight control should be an essential part of treatment. We found men with osteoarthritis to have had an IWL more often than men without the disease. In a BMI-specific analysis, the association was only significant in those who had overweight. It may be that these individuals previously had obesity but had succeeded in losing weight, whereas those with current obesity lack the association, due to not having succeeded. However, a suggestive association between osteoarthritis and also dieting attempts emerged in those who were overweight but not in those with obesity, which does not affirm the preceding speculation; and BMI-specific associations may also arise from small n-sizes in these categories in a population-based study. In our study, men with T2D or an osteoarthritis diagnosis may have taken the diagnosis as a serious warning sign to start losing weight in order to stop the progression of the disease. Women with the diagnosis may act alike; but as women already diet more often than men, the difference between the groups remains non-significant.
Our inverse finding between SOC and dieting attempts is the first on this topic. Individuals with low SOC values (i.e., those with a relatively poor capacity to cope with everyday life and to manage its stressors [43]) have previously been shown to be less successful in achieving health-related lifestyle changes and a better quality of life than persons with higher SOC values [76]. Thus, they may be prone to misperceiving their weight as a problematic issue, possibly due to their lack of resources to deal with other life issues perceived as too difficult to manage. Thus a dieting attempt may be used as a means to seek better overall control of one’s life instead of being content with oneself or focusing on making other attempts to change their negative dispositions. Alternatively, greater attempted dieting in persons with a low SOC might be seen as a sign of persons becoming aware that something in their lives needs to be changed.
Most of the reported motives that push people to attempt dieting are related to appearance and health reasons [12]. In this study, the determinants studied were not asked about as motives or strategies for dieting but as independent factors, so it is impossible to specify whether the determinants are actually reasons for dieting or only associated with them. However, it can be speculated that individuals reporting concerns about their appearance or health attempt dieting because of these factors. Those having concerns about their appearance or health reported more dieting attempts but not more IWL. Such concerns may be a reason for dieting, but as they are only associated with dieting attempts and not with weight loss, they may not be such a strong reason to actually lose weight. The association between concerns for one’s appearance and dieting attempts was slightly pronounced in women, whereas the association between concerns for one’s health and dieting attempts was more pronounced in men. Such a tendency is in line with men with a disease diagnosis (T2D or osteoarthritis) dieting more commonly. In a study conducted with women, those trying to lose weight and motivated by appearance reasons used more unhealthy dieting strategies (e.g., skipping meals, eating only one type of food, vomiting, using laxatives and diuretics) and also reported more lapses, whereas those motivated by health reasons used healthier strategies [77]. When looking into associations between concerns about one’s appearance and dieting attempts in BMI categories, the association only appeared in those with normal weight and those who had overweight. It might be that appearance concerns are more present in the lives of those with lower BMI, while, along with a higher BMI, health-related reasons become more relevant.
The present study contains some major strengths, as follows: The large representative adult population sample; a comprehensive set of potential determinants covering demographic, lifestyle, somatic health, and psychiatric and psychological factors; the availability of body composition-related measures and biomarkers; and the simultaneous exploration of dieting attempts and IWL.
However, there are also some limitations. First, because of the cross-sectional study design, it remains unresolved whether dieting attempts and IWL are a cause or a consequence of the determinants or are associated with the determinants for some other reason. Second, as the dieting variables were self-reported, the concept, seriousness, and continuity of dieting may vary between individuals, making the dieters’ group heterogeneous. That may affect the interpretation of the results. Third, we included all individuals attempting dieting with previous weight loss in the IWL group, hence the range of self-reported weight loss is quite extensive (range 1–38 kg, mean 5.43 (SD 4.21) kg). Fourth, we did not exclude individuals with cancer, T2D, or any other disease from the sample, although these individuals may have attempted dieting and experienced unintentional weight loss. Fifth, the small number of subjects in the categories of certain determinants, including somatic diseases and psychiatric disorders, makes the distributions of these variables skewed; thus, possibly masking associations. Sixth, even though we included a vast set of possible determinants in our scrutiny, other important determinants may be missing. Seventh, the inclusion of all potential determinants in the final models may have caused overadjustment. Finally, due to the numerous analyses conducted, the possibility of false positive findings cannot be ruled out.

5. Conclusions

This study was among the first to concentrate on a comprehensive scrutiny of the determinants of self-report dieting attempts and IWL. Dieting attempts were common in women within every BMI category; whereas in men with normal weight, they were relatively infrequent. Moreover, the prevalence of IWL grew along with BMI in men but not in women. It seems that in women, dieting behaviour is not that dependent on a real need to lose weight, while it seems that men do not start dieting until they become affected by overweight or develop an obesity-related disease (such as T2D or osteoarthritis).
The exploration of the determinants associated with dieting attempts and IWL is important in regard to their use as confounding factors when analyzing the associations between dieting attempts and the incidence of chronic diseases. Moreover, these findings can be used for determining subgroups with obesity that would benefit from weight loss but abstain from dieting. Simultaneously, subpopulations with normal weight attempting dieting can be revealed, which is important in order to plan preventive actions against unnecessary dieting attempts and possible future weight gain. Further studies and meta-analyses, in particular, are needed to strengthen the information on the determinants of dieting attempts and IWL.

Supplementary Materials

The following is available online at https://www.mdpi.com/2072-6643/11/8/1789/s1, Table S1: Self-report dieting attempts and IWL during the previous year by interaction of BMI and selected determinants.

Author Contributions

Conceptualization, L.S.-J., P.K., S.M., and M.H.; methodology, L.S.-J. and P.K.; formal analysis, L.S.-J.; investigation, L.S.-J.; data curation, L.S.-J.; writing—original draft preparation, L.S.-J.; writing—review and editing, L.S.-J., P.K., S.M., O.L., and M.H.; visualization, L.S.-J. and P.K.; project administration, L.S.-J. and P.K.; funding acquisition, L.S.-J.

Funding

This research was funded by The Doctoral Programme in Population Health, University of Helsinki (L.S.-J.) and by The Juho Vainio Foundation (L.S.-J.).

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript or in the decision to publish the results.

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Table
Table 1. Characteristics of the men and women in the study population.
Table 1. Characteristics of the men and women in the study population.
Men and Women (n = 4525) Men (n = 2147) Women (n = 2378)
DeterminantsnMean (SD) or %nMean (SD) or %nMean (SD) or %
Dieting
Dieting attempts * (%)452531.8214724.2237838.6
IWL * (%)452513.0214710.4237815.3
Socio-demographic factors
Age (years)452547.9 (10.7)214747.7 (10.6)237848.0 (10.8)
High education (%)451332.4214126.6237237.6
Lifestyle related factors
BMI (kg/m2)452526.8 (4.68)214727.1 (4.12)237826.5 (5.11)
FFMI (fat free mass kg/m2)438219.3 (2.41)209521.0 (1.90)228717.8 (1.70)
Regular vigorous training (%)449819.1213322.2236516.2
Sitting time (min/day)4363340 (169)2082340 (176)2281340 (162)
Current smoking (%)451030.2214035.5237025.3
Energy intake (kcal/day)42212304 (791)19752408 (827)22462213 (746)
AHEI (score) (range 7–35)422121.2 (4.94)197521.1 (4.96)224621.3 (4.91)
Daily consuming sweets, chocolate, cookies, dried fruits or sugar-sweetened drinks (%)451322.5214326.7237018.7
Sleep duration (hours)42247.46 (1.04)19817.33 (1.02)22437.57 (1.05)
Somatic health
Fs-triglycerides (mmol/L)45101.57 (1.06)21421.83 (1.31)23681.33 (0.69)
Fs-HDL (mmol/L)45101.34 (0.38)21421.21 (0.33)23681.45 (0.38)
Elevated blood pressure † (%)452555.9214764.4237848.2
T2D (%)45253.5421473.8723783.24
Osteoarthritis (%)44674.8821315.2123364.58
Psychological factors
SOC (mean score) (range 1–7)43145.48 (0.80)20235.50 (0.81)22915.46 (0.80)
Concerns about one’s appearance (%)447116.6212711.1234421.6
Concerns about one’s health (%)448030.9212528.1235533.3
n, Number of subjects in respective category; SD, Standard deviation; IWL, Intentional weight loss; BMI, Body mass index; FFMI, Fat free mass index; AHEI, Alternate Healthy Eating Index; Fs-, Fasting serum; HDL, High density lipoprotein; T2D, Type 2 diabetes; SOC, Sense of coherence. * During the previous year. † Systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg, or use of antihypertensive medication.
Table
Table 2. Self-report dieting attempts during the previous year in men and women by potential determinants (n = 4525).
Table 2. Self-report dieting attempts during the previous year in men and women by potential determinants (n = 4525).
Men and Women (n = 4525) Men (n = 2147) Women (n = 2378) p for Inter-Action by Sex
Age and Sex-Adjusted Full Model * Age-Adjusted Full Model * Age-Adjusted Full Model *
Determinantsn(%)nOR95% CIn(%)nOR95% CIn(%)nOR95% CI
Socio-demographic factors
Age (years)4525 3749 2147 1780 2378 1969 0.02
 30–39122731.610551 58321.44891 64440.75661
 40–49132733.811190.830.68–1.0262926.95351.070.77–1.4969840.15840.700.54–0.92
 50–59117632.99700.580.46–0.7257424.74750.630.43–0.9060240.44950.540.40–0.74
 60–6979527.06050.450.34–0.6036123.32810.630.41–0.9943430.63240.370.25–0.55
 p for trend † 0.14 0.40 0.009
Education (%)4513 3749 2141 1780 2372 1969 0.37
 Low145029.811081 69122.15301 75936.95781
 Intermediate160330.913661.100.90–1.3588123.17531.100.80–1.5072238.36131.130.86–1.48
 High146034.812751.391.12–1.7256928.54971.631.15–2.3189140.47781.260.96–1.65
 p for heterogeneity 0.01 0.02 0.39
Lifestyle related factors
BMI (kg/m2)4525 3749 2147 1780 2378 1969 <0.0001
 <25174614.814551 6926.285691 105422.28861
 25–29.9180536.215172.521.99–3.19101026.28544.172.69–6.4779545.76632.201.64–2.95
 ≥3097454.17774.243.03–5.9344547.63579.545.33–17.152960.54202.811.83–4.31
 p for trend † <0.0001 <0.0001 <0.0001
FFMI quintiles ‡ (fat free mass kg/m2)4382 3749 2095 1780 2287 1969 0.001
 1st (lowest)87512.87521 4196.243441 45618.34081
 2nd87724.17451.541.16–2.0541917.93571.951.15–3.3145829.53881.431.01–2.02
 3rd87632.07541.551.16–2.0841921.93691.660.97–2.8645741.33851.601.11–2.30
 4th87640.17531.641.18–2.2641931.73612.031.14–3.6045748.03921.450.97–2.17
 5th87850.47451.080.72–1.6241943.53491.490.76–2.9245957.43960.820.48–1.40
 p for trend <0.0001 <0.0001 <0.0001
Leisure-time physical activity4498 3749 2133 1780 2365 1969 0.38
 Low110829.49001 54321.34391 56536.94611
 Moderate253331.920971.401.15–1.70111725.19191.611.17–2.22141638.111781.280.99–1.64
 Regular vigorous training85735.27521.651.29–2.0947325.94221.701.18–2.4738443.93301.691.22–2.34
 p for heterogeneity 0.02 0.16 0.07
Sitting time tertiles § (min/day)4363 3749 2082 1780 2281 1969 0.45
 1st (lowest)144429.212111 67722.05571 76735.76541
 2nd141830.512251.060.88–1.2869322.76041.120.82–1.5272537.76211.070.83–1.37
 3rd150135.813131.301.08–1.5771228.16191.481.09–2.0278942.76941.200.94–1.53
 p for trend 0.0001 0.008 0.004
Smoking4510 3749 2140 1780 2370 1969 0.60
 Never220731.218601 77923.36631 142838.511971
 Former smoker94339.77881.281.05–1.5660130.55011.060.78–1.4334248.02871.421.07–1.89
 Current smoker136027.211010.880.73–1.0776019.96160.830.61–1.1260033.64850.880.69–1.13
 p for heterogeneity <0.0001 <0.0001 <0.0001
Energy intake quintiles ‖ (kcal/day) 4221 3749 1975 1780 2246 1969 0.26
 1st (lowest)84437.07351 39528.83511 44944.03841
 2nd84433.37550.860.68–1.0939528.63581.150.80–1.6544937.43970.680.50–0.94
 3rd84430.17430.740.58–0.9439521.83490.750.51–1.1044937.43940.730.53–1.00
 4th84430.97580.760.60–0.9639523.33570.790.54–1.1644937.64010.740.54–1.01
 5th84528.97580.600.47–0.7739520.33650.620.42–0.9245036.73930.590.43–0.83
 p for trend 0.0002 0.001 0.05
AHEI quintiles 4221 3749 1975 1780 2246 1969 0.67
 1st (lowest)75922.96531 37315.83231 38629.23301
 2nd83527.67421.371.05–1.7839020.03541.370.89–2.1144534.43881.350.96–1.89
 3rd97031.48701.451.13–1.8843625.23931.701.12–2.5853436.94771.320.95–1.83
 4th78734.97041.701.31–2.2336927.43381.801.17–2.7741841.53661.601.13–2.26
 5th87042.27802.261.74–2.9540733.73722.181.43–3.3346349.84082.291.62–3.23
 p for trend <0.0001 <0.0001 <0.0001
Daily consuming certain sugary products **4513 3749 2143 1780 2370 1969 0.23
 No349933.929251 157126.113101 192841.016151
 Yes101424.28240.730.60–0.8957218.94700.850.63–1.1344228.43540.610.46–0.81
 p for heterogeneity <0.0001 0.0007 <0.0001
Sleep duration (hours)4224 3749 1981 1780 2243 1969 0.01
 ≤658334.64911 31630.72661 26737.52251
 7–8317031.828660.840.67–1.05150923.313810.600.44–0.83166139.314851.130.82–1.56
 ≥947130.93920.780.57–1.0715625.51330.720.43–1.2231536.02590.940.62–1.42
 p for heterogeneity 0.34 0.02 0.50
Somatic health
Fs-triglycerides (mmol/L)4510 3749 2142 1780 2368 1969 0.59
 <1.7309527.925841 126720.010441 182835.115401
 ≥1.7141540.211651.201.00–1.4487530.47361.050.81–1.3754050.54291.401.07–1.82
 p for heterogeneity <0.0001 <0.0001 <0.0001
Fs-HDL (mmol/L)4510 3749 2142 1780 2368 1969 0.56
 ≥1.03 in men or ≥1.29 in women296827.824781 147721.212351 149133.812431
 <1.03 in men or  <1.29 in women154239.312711.180.99–1.4066530.95451.020.77–1.3587746.77261.271.02–1.58
 p for heterogeneity <0.0001 <0.0001 <0.0001
Elevated blood pressure ††4525 3749 2147 1780 2378 1969 0.12
 No199527.516911 76419.96421 123134.110491
 Yes253035.120580.970.82–1.16138326.611380.980.75–1.29114743.49200.990.78–1.24
 p for heterogeneity <0.0001 0.0007 <0.0001
T2D4525 3749 2147 1780 2378 1969 0.02
 No436531.136331 206423.317151 230138.119181
 Yes16051.11161.430.94–2.198346.9652.131.20–3.787754.2510.860.46–1.61
 p for heterogeneity <0.0001 <0.0001 0.005
Knee or hip osteoarthritis4467 3749 2131 1780 2336 1969 0.26
 No424931.335821 202023.517021 222938.318801
 Yes21841.41670.920.63–1.3411134.9780.960.54–1.6910747.0890.890.54–1.45
 p for heterogeneity 0.002 0.008 0.08
Psychological factors
SOC quartiles ‡‡4314 3749 2023 1780 2291 1969 0.79
 1st (highest)113328.810031 54323.45001 59033.45031
 2nd112730.510070.990.80–1.2255822.65020.950.68–1.3256937.75051.070.81–1.41
 3rd104533.59231.070.86–1.3342825.93770.950.66–1.3561740.15461.180.89–1.55
 4th (lowest)100936.88161.451.15–1.8249427.74011.400.98–1.9951545.04151.471.08–2.00
 p for trend <0.0001 0.06 <0.0001
Concerns about one’s appearance4471 3749 2127 1780 2344 1969 0.59
 Does not feel that looks any worse than used to372930.331441 189123.116031 183836.815411
 Concerns about one’s appearance74240.16051.271.03–1.5823633.41771.290.87–1.9350646.24281.291.00–1.66
 p for heterogeneity <0.0001 0.0006 0.0001
Concerns about one’s health4480 3749 2125 1780 2355 1969 0.18
 Not worried about their health more than usually309729.126171 152721.712961 157035.813211
 Concerns about one’s health138338.211321.211.02–1.4359830.74841.371.04–1.8178544.96481.170.94–1.47
 p for heterogeneity <0.0001 <0.0001 <0.0001
n, Number of subjects in respective category; OR, Odds ratio; CI, Confidence interval; BMI, Body mass index; FFMI, Fat free mass index; AHEI, Alternate Healthy Eating Index; Fs-, Fasting serum; HDL, High density lipoprotein; T2D, Type 2 diabetes; SOC, Sense of coherence. Bolded results are statistically significant. * Adjusted for all the other variables in the table: sex (only when men and women analyzed together), age (continuous), education, BMI (continuous), FFMI (continuous as quintiles), leisure-time physical activity, sitting time (continuous as tertiles), smoking, energy intake (continuous as quintiles), AHEI (continuous as quintiles), daily consuming certain sugary products, sleep duration, fs-triglycerides, fs-HDL, elevated blood pressure, T2D, osteoarthritis, SOC (continuous as quartiles), concerns about one’s appearance, and concerns about one’s health. † Trend for continuous variable. ‡ FFMI quintile ranges (fat free mass kg/m2): 1st 14.3–19.5 for male, 11.1–16.3 for female; 2nd 19.6–20.5 for male, 16.4–17.2 for female; 3rd 20.6–21.4 for male, 17.3–18.1 for female; 4th 21.5–22.6 for male, 18.2–19.2 for female; 5th 22.7–29.4 for male, 19.3–24.2 for female. § Sitting time tertile ranges (min): 1st 0–236 for male, 0–240 for female; 2nd 237–381 for male, 241–390 for female; 3rd 382–1200 for male, 391–1311 for female. ‖ Energy intake quintile ranges (kcal): 1st 688–1745 for male, 593–1613 for female; 2nd 1746–2097 for male, 1614–1942 for female; 3rd 2098–2467 for male, 1943–2285 for female; 4th 2468–3013 for male, 2286–2692 for female; 5th 3014–6413 for male, 2693–6495 for female. AHEI quintile ranges (points): 1st 7–16 for male, 7–16 for female; 2nd 17–19 for male, 17–19 for female; 3rd 20–22 for male, 20–22 for female; 4th 23–25 for male, 23–25 for female; 5th 26–34 for male, 26–35 for female. ** Daily consumption of juices, lemonades, hot chocolate, toffee, licorice, dried fruit (e.g., raisins), sweets, hard pastilles, or candy without xylitol, chocolate, or filled biscuits. †† Systolic blood pressure ≥130 mmHg, or diastolic blood pressure ≥85 mmHg, or use of antihypertensive medication. ‡‡ SOC quartile ranges (score):1st 1.50–5.00 for male, 2.25–4.83 for female; 2nd 5.01–5.50 for male, 4.84–5.50 for female; 3rd 5.51–6.00 for male, 5.51–6.00 for female; 4th 6.01–7.00 for male, 6.01–7.00 for female.
Table
Table 3. Self-report IWL during the previous year in men and women by potential determinants (n = 4525).
Table 3. Self-report IWL during the previous year in men and women by potential determinants (n = 4525).
Men and Women (n = 4525) Men (n = 2147) Women (n = 2378) p for Inter-Action by Sex
Age and Sex-Adjusted Full Model * Age-Adjusted Full Model * Age-Adjusted Full Model *
Determinantsn(%)nOR95% CIn(%)nOR95% CIn(%)nOR95% CI
Socio-demographic factors
Age (years)4525 3749 2147 1780 2378 1969 0.05
 30–39122714.810551 5839.434891 64419.65661
 40–49132713.711190.750.58–0.9762911.95351.050.69–1.6069815.35840.580.42–0.82
 50–59117613.19700.620.46–0.8357410.34750.680.42–1.0960215.64950.560.38–0.82
 60–697958.706050.420.29–0.623619.422810.640.35–1.154348.293240.320.19–0.53
 p for trend † 0.0002 0.83 <0.0001
Education (%)4513 3749 2141 1780 2372 1969 0.23
 Low145011.311081 6919.675301 75913.05781
 Intermediate160312.613661.140.87–1.508819.437531.030.68–1.5672215.86131.270.89–1.81
 High146015.012751.401.07–1.8556912.74971.530.97–2.4089116.87781.350.95–1.92
 p for heterogeneity 0.02 0.11 0.13
Lifestyle related factors
BMI (kg/m2)4525 3749 2147 1780 2378 1969 0.01
 <2517467.3714551 6923.835691 105410.28861
 25–29.9180514.315171.300.95–1.78101011.98543.071.71–5.5079516.46630.860.58–1.27
 ≥3097420.47771.490.97–2.3044517.13574.442.03–9.6752923.74200.870.51–1.49
 p for trend † <0.0001 <0.0001 <0.0001
FFMI quintiles (fat free mass kg/m2) ‡4382 3749 2095 1780 2287 1969 0.53
 1st (lowest)8755.687521 4193.803441 4566.994081
 2nd8779.627451.450.98–2.154197.633571.350.68–2.7045811.23881.590.98–2.57
 3rd87613.07541.621.10–2.4041910.33691.580.80–3.1345715.53851.771.09–2.90
 4th87616.47531.951.29–2.9541914.43612.000.99–4.0545718.43921.991.18–3.36
 5th87820.07451.590.96–2.6441915.73491.130.48–2.6645924.43962.201.14–4.25
 p for trend <0.0001 <0.0001 <0.0001
Leisure-time physical activity4498 3749 2133 1780 2365 1969 0.84
 Low110811.29001 5439.184391 56513.14611
 Moderate 253313.420971.351.04–1.74111710.89191.450.96–2.19141615.811781.300.94–1.81
 Regular vigorous training85714.17521.310.96–1.7947311.04221.390.85–2.2638417.13301.310.86–1.99
 p for heterogeneity 0.10 0.55 0.19
Sitting time tertiles § (min/day)4363 3749 2082 1780 2281 1969 0.48
 1st (lowest)144411.212111 6778.715571 76713.36541
 2nd141812.812251.180.92–1.5269310.36041.400.93–2.1272515.26211.100.79–1.52
 3rd150115.213131.381.08–1.7771211.96191.581.04–2.4078918.26941.300.96–1.78
 p for trend 0.001 0.05 0.008
Smoking4510 3749 2140 1780 2370 1969 0.64
 Never220711.518601 7798.166631 142814.611971
 Former smoker94317.17881.451.13–1.8860113.75011.380.91–2.0934219.42871.481.05–2.09
 Current smoker136012.511011.250.98–1.597609.876161.460.98–2.1760014.74851.100.80–1.50
 p for heterogeneity 0.0001 0.004 0.08
Energy intake quintiles ‖ (kcal/day) 4221 3749 1975 1780 2246 1969 0.56
 1st (lowest)84415.67351 39512.73511 44917.93841
 2nd84413.27550.810.60–1.1039511.73581.100.68–1.7844914.43970.650.44–0.97
 3rd84412.47430.780.57–1.063958.633490.800.47–1.3444915.63940.760.52–1.13
 4th84413.57580.870.64–1.1839510.83570.960.58–1.5944916.04010.770.52–1.14
 5th84510.67580.660.48–0.913959.043650.880.52–1.4745012.33930.550.36–0.84
 p for trend 0.008 0.10 0.07
AHEI quintiles 4221 3749 1975 1780 2246 1969 0.70
 1st (lowest)7598.536531 3736.853231 3869.953301
 2nd83510.67421.350.94–1.943907.613541.110.61–2.0244513.23881.500.95–2.37
 3rd97012.48701.360.96–1.9243610.63931.370.78–2.4153414.14771.350.87–2.10
 4th78714.17041.591.11–2.2736912.03381.650.93–2.9241815.93661.480.93–2.37
 5th87019.17802.211.56–3.1240715.63721.871.07–3.2846322.24082.421.54–3.79
 p for trend <0.0001 <0.0001 <0.0001
Daily consuming certain sugary products **4513 3749 2143 1780 2370 1969 1.00
 No349914.129251 157111.513101 192816.416151
 Yes10148.898240.730.56–0.965727.124700.760.51–1.1344210.53540.730.50–1.07
 p for heterogeneity <0.0001 0.003 0.002
Sleep duration (hours)4224 3749 1981 1780 2243 1969 0.03
 ≤658313.34911 31613.92661 26712.22251
 7–8317013.328660.930.69–1.25150910.113810.630.42–0.95166116.014851.330.85–2.06
 ≥947111.63920.940.63–1.411569.631330.790.40–1.5731513.12591.220.71–2.11
 p for heterogeneity 0.60 0.13 0.14
Somatic health
Fs-triglycerides (mmol/L)4510 3749 2142 1780 2368 1969 0.83
 <1.7309512.225841 12679.7010441 182814.415401
 ≥1.7141514.511650.850.67–1.0787511.37360.810.57–1.1554018.24290.950.68–1.32
 p for heterogeneity 0.04 0.23 0.04
Fs-HDL (mmol/L)4510 3749 2142 1780 2368 1969 0.67
 ≥1.03 in men or ≥1.29 in women296811.224781 14779.4112351 149112.812431
 <1.03 in men or <1.29 in women154216.212711.331.07–1.6566512.55451.170.81–1.6887719.47261.431.08–1.88
 p for heterogeneity <0.0001 0.03 <0.0001
Elevated blood pressure ††4525 3749 2147 1780 2378 1969 0.77
 No199511.816911 76410.06421 123113.210491
 Yes253013.920581.020.81–1.27138310.611380.860.60–1.23114717.59201.170.88–1.57
 p for heterogeneity 0.05 0.68 0.008 0.28
T2D4525 3749 2147 1780 2378 1969 0.11
 No436512.636331 20649.8717151 230115.019181
 Yes16023.01161.600.99–2.588323.2652.161.13–4.157722.2511.070.52–2.21
 p for heterogeneity 0.0001 0.0001 0.09
Knee or hip osteoarthritis4467 3749 2131 1780 2336 1969 0.03
 No424912.635821 20209.7117021 222915.318801
 Yes21820.31671.530.99–2.3811121.5782.271.21–4.2910718.6891.040.55–1.96
 p for heterogeneity 0.001 0.0001 0.36
Psychological factors
SOC quartiles ‡‡4314 3749 2023 1780 2291 1969 0.42
 1st (highest)113312.910031 54311.25001 59014.35031
 2nd112713.710071.000.76–1.3055811.35021.030.68–1.5656916.05051.000.70–1.43
 3rd104512.39230.830.62–1.104289.133770.590.35–0.9761714.95460.970.68–1.38
 4th (lowest)100913.58161.060.79–1.4249410.64010.990.63–1.5851516.14151.090.74–1.61
 p for trend 0.95 0.51 0.52
Concerns about one’s appearance4471 3749 2127 1780 2344 1969 0.07
 Does not feel that looks any worse than used to372912.631441 18919.9316031 183815.115411
 Concerns about one’s appearance74215.46051.100.84–1.4423614.51771.530.93–2.5350616.84280.970.70–1.34
 p for heterogeneity 0.04 0.03 0.35
Concerns about one’s health4480 3749 2125 1780 2355 1969 0.93
 Not worried about their health more than usually309712.326171 152710.112961 157014.313211
 Concerns about one’s health138314.511321.000.80–1.2559811.34840.910.62–1.3478517.36481.100.83–1.46
 p for heterogeneity 0.05 0.42 0.06
IWL, Intentional weight loss; n, Number of subjects in respective category; OR, Odds ratio; CI, Confidence interval; BMI, Body mass index; FFMI, Fat free mass index; AHEI, Alternate Healthy Eating Index; Fs-, Fasting serum; HDL, High density lipoprotein; T2D, Type 2 diabetes; SOC, Sense of coherence. Bolded results are statistically significant. * Adjusted for all the other variables in the table: sex (only when men and women analyzed together), age (continuous), education, BMI (continuous), FFMI (continuous as quintiles), leisure-time physical activity, sitting time (continuous as tertiles), smoking, energy intake (continuous as quintiles), AHEI (continuous as quintiles), daily consuming certain sugary products, sleep duration, fs-triglycerides, fs-HDL, elevated blood pressure, T2D, osteoarthritis, SOC (continuous as quartiles), concerns about one’s appearance, and concerns about one’s health. † Trend for continuous variable. ‡ FFMI quintile ranges (fat free mass kg/m2): 1st 14.3–19.5 for male, 11.1–16.3 for female; 2nd 19.6–20.5 for male, 16.4–17.2 for female; 3rd 20.6–21.4 for male, 17.3–18.1 for female; 4th 21.5–22.6 for male, 18.2–19.2 for female; 5th 22.7–29.4 for male, 19.3–24.2 for female. § Sitting time tertile ranges (min): 1st 0–236 for male, 0–240 for female; 2nd 237–381 for male, 241–390 for female; 3rd 382–1200 for male, 391–1311 for female. ‖ Energy intake quintile ranges (kcal): 1st 688–1745 for male, 593–1613 for female; 2nd 1746–2097 for male, 1614–1942 for female; 3rd 2098–2467 for male, 1943–2285 for female; 4th 2468–3013 for male, 2286–2692 for female; 5th 3014–6413 for male, 2693–6495 for female. AHEI quintile ranges (points): 1st 7–16 for male, 7–16 for female; 2nd 17–19 for male, 17–19 for female; 3rd 20–22 for male, 20–22 for female; 4th 23–25 for male, 23–25 for female; 5th 26–34 for male, 26–35 for female. ** Daily consuming juices, lemonades, hot chocolate, toffee, licorice, dried fruit, e.g., raisins, sweets, hard pastilles, or candy without xylitol, chocolate, or filled biscuits. †† Systolic blood pressure ≥130 mmHg, or diastolic blood pressure ≥85 mmHg, or use of antihypertensive medication. ‡‡ SOC quartile ranges (score):1st 1.50–5.00 for male, 2.25–4.83 for female; 2nd 5.01–5.50 for male, 4.84–5.50 for female; 3rd 5.51–6.00 for male, 5.51–6.00 for female; 4th 6.01–7.00 for male, 6.01–7.00 for female.

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MDPI and ACS Style

Sares-Jäske, L.; Knekt, P.; Männistö, S.; Lindfors, O.; Heliövaara, M. Self-Report Dieters: Who Are They? Nutrients 2019, 11, 1789. https://doi.org/10.3390/nu11081789

AMA Style

Sares-Jäske L, Knekt P, Männistö S, Lindfors O, Heliövaara M. Self-Report Dieters: Who Are They? Nutrients. 2019; 11(8):1789. https://doi.org/10.3390/nu11081789

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Sares-Jäske, Laura, Paul Knekt, Satu Männistö, Olavi Lindfors, and Markku Heliövaara. 2019. "Self-Report Dieters: Who Are They?" Nutrients 11, no. 8: 1789. https://doi.org/10.3390/nu11081789

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