Misreporting and misclassification: implications for socioeconomic disparities in body-mass index and obesity

The hidden cost of sophistication: economic complexity and obesity

Obesity has become a global health crisis, affecting people of all ages, regions, and socio-economic backgrounds. While individual behaviour and genetic factors contribute to obesity, the role of economic complexity in the evolution of obesity rates has not yet been empirically studied. Using a large panel of 110 countries over the period 1976-2015, this article estimates the linear and non-linear links between obesity and economic complexity. According to baseline results, an improvement in economic complexity will lead to an increase in obesity up to a certain threshold. Beyond this turning point, any further increase in economic complexity will significantly contribute to obesity reduction. The issue of simultaneity is tackled using the two-stage instrumental variable method. Our findings support the Obesity Kuznets Curve (OKC) pattern, which suggests that economic progress and obesity have an inverted U-shaped relationship. Our results suggest that greater embeddedness of knowledge in the products produced and exported by a country increases the likelihood of obesity in society, at least up to a threshold. From these results, some important policy implications are discussed.

Effects of changes in residential fast-food outlet exposure on Body Mass Index change: longitudinal evidence from 92,211 Lifelines participants

BACKGROUND

Evidence on the association between fast-food outlet exposure and Body Mass Index (BMI) remains inconsistent and is primarily based on cross-sectional studies. We investigated the associations between changes in fast-food outlet exposure and BMI changes, and to what extent these associations are moderated by age and fast-food outlet exposure at baseline.

METHODS

We used 4-year longitudinal data of the Lifelines adult cohort (N = 92,211). Participant residential addresses at baseline and follow-up were linked to a register containing fast-food outlet locations using geocoding. Change in fast-food outlet exposure was defined as the number of fast-food outlets within 1 km of the residential address at follow-up minus the number of fast-food outlets within 1 km of the residential address at baseline. BMI was calculated based on objectively measured weight and height. Fixed effects analyses were performed adjusting for changes in covariates and potential confounders. Exposure-moderator interactions were tested and stratified analyses were performed if p < 0.10.

RESULTS

Participants who had an increase in the number of fast-food outlets within 1 km had a greater BMI increase (B(95% CI): 0.003 (0.001,0.006)). Decreases in fast-food outlet exposure were not associated with BMI change (B(95% CI): 0.001 (-0.001,0.004)). No clear moderation pattern by age or fast-food outlet exposure at baseline was found.

CONCLUSIONS

Increases in residential fast-food outlet exposure are associated with BMI gain, whereas decreases in fast-food outlet exposure are not associated with BMI loss. Effect sizes of increases in fast-food outlet exposure on BMI change were small at individual level. However, a longer follow-up period may have been needed to fully capture the impact of increases in fast-food outlet exposure on BMI change. Furthermore, these effect sizes could still be important at population level considering the rapid rise of fast-food outlets across society. Future studies should investigate the mechanisms and changes in consumer behaviours underlying associations between changes in fast-food outlet exposure and BMI change.

Waist-to-hip circumference and waist-to-height ratio could strongly predict glycemic control than body mass index among adult patients with diabetes in Ethiopia: ROC analysis

Background

Poorly controlled blood glucose is prevalent and contributes to the huge burden of diabetes related morbidity, and central obesity has a great role in the pathogenesis of diabetes and its adverse complications, which could predict such risks, yet evidence is lacking. Hence, this paper is to evaluate the predictive performance of central obesity indices for glycemic control among adult patients with diabetes in eastern Ethiopia.

Methods

A survey of 432 randomly chosen patients with diabetes was conducted using a pretested questionnaire supplemented by chart review, anthropometrics, and biomarkers by trained data collectors. The poor glycemic control was assessed using a fasting blood glucose (FBS) level of above 130 and/or an HgA1c level above 7%. Weight, height, waist circumference (WC), and hip circumference (HC) were measured under standard procedures and we calculated waist-to-hip circumference ratio (WHR) and waist-to-height ratio (WHtR). The receiver operating characteristics curve was used to assess the predictive performance of obesity indices for glycemic control using area under the curve (AUC) and corresponding validity measures.

Results

A total of 432 (92%) patients with diabetes were enrolled with a mean age of 49.6 (±12.4) years. The mean fasting blood glucose level was 189 (±72) mg dl-1 where 330 (76.4%) (95% CI: 74.4–78.4%) and 93.3% of them had poor glycemic control based on FBS and HgA1c, respectively. WC (AUC = 0.90; 95% CI: 0.85–0.95), WHR (AUC = 0.64; 95% CI: 0.43–0.84), and WHtR (AUC = 0.87; 95% CI: 0.83–0.94) have a higher predictive performance for poor glycemic control at cut-off points above 100 cm, 0.95, and 0.62, respectively. However, obesity indices showed a lower predictive performance for poor glycemic control based on FBS. Body mass index (BMI) had a poor predictive performance for poor glycemic control (AUC = 0.26; 95% CI: 0.13–0.40).

Conclusions

Poor glycemic control is a public health concern and obesity indicators, typically WC, WHR, and WHtR, have a better predictive performance for poor glycemic control than BMI.

The association between the presence of fast-food outlets and BMI: the role of neighbourhood socio-economic status, healthy food outlets, and dietary factors

Background

Evidence on the association between the presence of fast-food outlets and Body Mass Index (BMI) is inconsistent. Furthermore, mechanisms underlying the fast-food outlet presence-BMI association are understudied. We investigated the association between the number of fast-food outlets being present and objectively measured BMI. Moreover, we investigated to what extent this association was moderated by neighbourhood socio-economic status (NSES) and healthy food outlets. Additionally, we investigated mediation by frequency of fast-food consumption and amount of fat intake.

Methods

In this cross-sectional study, we used baseline data of adults in Lifelines (N = 149,617). Geo-coded residential addresses were linked to fast-food and healthy food outlet locations. We computed the number of fast-food and healthy food outlets within 1 kilometre (km) of participants’ residential addresses (each categorised into null, one, or at least two). Participants underwent objective BMI measurements. We linked data to Statistics Netherlands to compute NSES. Frequency of fast-food consumption and amount of fat intake were measured through questionnaires in Lifelines. Multivariable multilevel linear regression analyses were performed to investigate associations between fast-food outlet presence and BMI, adjusting for individual and environmental potential confounders. When exposure-moderator interactions had p-value < 0.10 or improved model fit (∆AIC ≥ 2), we conducted stratified analyses. We used causal mediation methods to assess mediation.

Results

Participants with one fast-food outlet within 1 km had a higher BMI than participants with no fast-food outlet within 1 km (B = 0.11, 95% CI: 0.01, 0.21). Effect sizes for at least two fast-food outlets were larger in low NSES areas (B = 0.29, 95% CI: 0.01, 0.57), and especially in low NSES areas where at least two healthy food outlets within 1 km were available (B = 0.75, 95% CI: 0.19, 1.31). Amount of fat intake, but not frequency of fast-food consumption, explained this association for 3.1%.

Conclusions

Participants living in low SES neighbourhoods with at least two fast-food outlets within 1 km of their residential address had a higher BMI than their peers with no fast-food outlets within 1 km. Among these participants, healthy food outlets did not buffer the potentially unhealthy impact of fast-food outlets. Amount of fat intake partly explained this association. This study highlights neighbourhood socio-economic inequalities regarding fast-food outlets and BMI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13826-1.

Clinical, immunological and virological SARS-CoV-2 phenotypes in obese and non-obese military health system beneficiaries

Background

The mechanisms underlying the association between obesity and coronavirus disease 2019 (COVID-19) severity remain unclear. After verifying that obesity was a correlate of severe COVID-19 in US Military Health System (MHS) beneficiaries, we compared immunological and virological phenotypes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in both obese and nonobese participants.

Methods

COVID-19–infected MHS beneficiaries were enrolled, and anthropometric, clinical, and demographic data were collected. We compared the SARS-CoV-2 peak IgG humoral response and reverse-transcription polymerase chain reaction viral load in obese and nonobese patients, stratified by hospitalization, utilizing logistic regression models.

Results

Data from 511 COVID-19 patients were analyzed, among whom 24% were obese and 14% severely obese. Obesity was independently associated with hospitalization (adjusted odds ratio [aOR], 1.91; 95% confidence interval [CI], 1.15–3.18) and need for oxygen therapy (aOR, 3.39; 95% CI, 1.61–7.11). In outpatients, severely obese had a log₁₀ (1.89) higher nucleocapsid (N1) genome equivalents (GE)/reaction and log₁₀ (2.62) higher N2 GE/reaction than nonobese (P = 0.03 and P < .001, respectively). We noted a correlation between body mass index and peak anti-spike protein IgG in inpatients and outpatients (coefficient = 5.48, P < .001).

Conclusions

Obesity is a strong correlate of COVID-19 severity in MHS beneficiaries. These findings offer new pathophysiological insights into the relationship between obesity and COVID-19 severity.

Income in relation to obesity measures in an East German adult population: findings from the LIFE-Adult-Study

Background

Obesity has been postulated to be a consequence of economic disadvantage. However, epidemiological studies failed to demonstrate a consistent link between income and body fat indicators. We examined income as a possible cause of obesity in an East German general population, focusing on appropriate representation of study variables, as well as on confounding and modification of the income-obesity association.

Methods

We used data of 9599 participants in the baseline examination of the LIFE-Adult-Study, conducted in the city of Leipzig from 2011 to 2014. Body mass index (BMI) and waist circumference (WC) as obesity measures were based on standardised measurements, net equivalised income (NEI) on self-reports. We estimated adjusted means of BMI and WC within NEI categories representing the range from risk of poverty to affluence. We stratified the analyses by gender, age, and education.

Results

A substantial part of the age-adjusted associations of income with obesity measures was attributable to other SES indicators. Adjusted for these variables, NEI was comparably associated with BMI and WC. Among women, BMI and WC decreased across NEI categories. The inverse associations tended to be stronger at non-working age (≥ 65 years) than at working age (< 65 years). Conversely, among working-age men, BMI and WC increased with increasing NEI. Among older men, risk of poverty was related to higher values of the obesity measures. The aforementioned associations were predominantly stronger in highly educated participants compared to those with medium/low education. The differences in mean BMI and WC between persons at risk of poverty and higher income groups were rather small, ranging from 1 to 2 kg/m² for BMI and 2 to 4 cm for WC.

Conclusions

Our investigation indicates an association between income and body fatness in an East German adult population that depends on the sociodemographic context of the people. However, it does not suggest that income disparities are a major driver of body fat accumulation in this population. Differential selection of study participants, error in the measurement of long-term income, and possibly reverse causality may have affected our conclusions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11302-w.

Debt and mental health: new insights about the relationship and the importance of the measure of mental health

BACKGROUND

Empirical research suggests that household debt and payment difficulties are detrimental to mental health. Despite well-known measurement problems that may contaminate analyses using subjective self-reported health measures, our knowledge is very limited concerning the effect of payment difficulties on 'objective' measures of mental health. Moreover, few studies use longitudinal data to examine the relationship. This study combines rich survey data and longitudinal data from administrative registers on a representative sample of the Swedish population to examine the relationship between payment difficulties and subjective and objective measures of mental health.

METHODS

We use data from a large survey of Swedish inhabitants (The Swedish Living Conditions Surveys) combined with data from administrative registers. We investigate both directions of the relationship between mental ill health and payment difficulties, controlling for previous mental health status and previous experiences of payment difficulties. We compare the association between payment difficulties and a self-reported measure of anxiety with the associations between payment difficulties and objective measures of mental ill health from a register of psychopharmaceutical drug consumption.

RESULTS

Payment difficulties associate with subjectively reported mental ill health, but less to psychopharmaca use. For objective measures, we find stronger evidence of a link running from mental ill health to later payment difficulties.

CONCLUSIONS

Self-reported and objective measures of mental problems may convey different messages regarding the impact of payment difficulties on mental health. Policy measures depend on whether the primary target group is individuals with severe mental problems or individuals with mild anxiety.

The Prevalence of Cardiovascular Risk Factors in Different Occupational Groups in New Zealand

OBJECTIVES

Although cardiovascular disease (CVD) risk has been shown to differ between occupations, few studies have specifically evaluated the distribution of known CVD risk factors across occupational groups. This study assessed CVD risk factors in a range of occupational groups in New Zealand, stratified by sex and ethnicity.

METHODS

Two probability-based sample surveys of the general New Zealand adult population (2004-2006; n = 3003) and of the indigenous people of New Zealand (Māori; 2009-2010; n = 2107), for which occupational histories and lifestyle factors were collected, were linked with routinely collected health data. Smoking, body mass index, deprivation, diabetes, high blood pressure, and high cholesterol were dichotomized and compared between occupational groups using age-adjusted logistic regression.

RESULTS

The prevalence of all known CVD risk factors was greater in the Māori survey than the general population survey, and in males compared with females. In general for men and women in both surveys 'Plant and machine operators and assemblers' and 'Elementary workers' were more likely to experience traditional CVD risk factors, while 'Professionals' were less likely to experience these risk factors. 'Clerks' were more likely to have high blood pressure and male 'Agricultural and fishery workers' in the general survey were less likely to have high cholesterol, but this was not observed in the Māori survey. Male Māori 'Trades workers' were less likely to have high cholesterol and were less obese, while for the general population survey, this was not observed.

CONCLUSIONS

This study showed differences in the distribution of known CVD risk factors across occupational groups, as well as between ethnic groups and males and females.

The role of financial strain and self-control in explaining health behaviours: the GLOBE study

Background

Why lower socioeconomic groups behave less healthily can only partly be explained by direct costs of behaving healthily. We hypothesize that low income increases the risk of facing financial strain. Experiencing financial strain takes up cognitive 'bandwidth' and leads to less self-control, and subsequently results in more unhealthy behaviour. We therefore aim to investigate (i) whether a low income increases the likelihood of experiencing financial strain and of unhealthy behaviours, (ii) to what extent more financial strain is associated with less self-control and, subsequently, (iii) whether less self-control is related to more unhealthy behaviour.

Methods

Cross-sectional survey data were obtained from participants (25-75 years) in the fifth wave of the Dutch GLOBE study (N = 2812) in 2014. The associations between income, financial strain, self-control and health-behaviour-related outcomes (physical inactivity in leisure-time, obesity, smoking, excessive alcohol intake, and weekly fruit and vegetable intake) were analysed with linear regression and generalized linear regression models (log link).

Results

Experiencing great compared with no financial strain increased the risk of all health-behaviour-related outcomes, independent of income. Low self-control, as compared with high self-control, also increased the risk of an unhealthy lifestyle. Taking self-control into account slightly attenuated the associations between financial strain and the outcomes.

Conclusion

Great financial strain and low self-control are consistently associated with unhealthy behaviours. Self-control may partly mediate between financial strain and unhealthy behaviour. Interventions that relieve financial strain may free up cognitive bandwidth and improve health behaviour.

Health disparities across education: The role of differential reporting error

One of the most robust findings in health economics is that higher educated individuals tend to be in better health. This paper tests whether health disparities across education are to some extent due to differences in reporting error across education. We test this hypothesis using data from the pooled National Health and Nutrition Examination Survey (NHANES) for 1999-2012, which include both self-reports and objective verification for an extensive set of health behaviors and conditions, including smoking, obesity, high blood pressure, high cholesterol, and diabetes. We find that college graduates are more likely to give false negative reports of obesity and high total cholesterol; one possible explanation for this is social desirability bias. However, college graduates are also significantly less likely to give false positive reports of smoking, obesity, and high cholesterol. Because there are far more truly negative people (who are less likely to give a false positive report) than more truly positive people (who are more likely to give a false negative report), we find that college graduates report their health significantly more accurately overall.

Is quality of life different between diabetic and non-diabetic people? The importance of cardiovascular risks

Background

To analyse and compare the impact of cardiovascular risk factors and disease on health-related quality of life (HRQoL) in people with and without diabetes living in the community.

Methods

We used data of 1,905 people with diabetes and 19,031 people without diabetes from the last Spanish National Health Survey (years 2011–2012). The HRQoL instrument used was the EuroQol 5D-5L, based on time trade-off scores. Matching methods were used to assess any differences in the HRQoL in people with and without diabetes with the same characteristics (age, gender, education level, and healthy lifestyle), according to cardiovascular risk factors and diseases. Disparities were also analysed for every dimension of HRQoL: mobility, daily activities, personal care, pain/discomfort, and anxiety/depression.

Results

There were no significant differences in time trade-off scores between people with and without diabetes when cardiovascular risk factors or established cardiovascular disease were not present. However, when cardiovascular risk factors were present, the HRQoL score was significantly lower in people with diabetes than in those without. This difference was indeed greater when cardiovascular diseases were present. More precisely, people with diabetes and any of the cardiovascular risk factors, who have not yet developed any cardiovascular disease, report lower HRQoL, 0.046 TTO score points over 1 (7.93 over 100 in the VAS score) compared to those without diabetes, and 0.14 TTO score points of difference (14.61 over 100 in the VAS score) if cardiovascular diseases were present. In fact, when the three risk factors were present in people with diabetes, HRQoL was significantly lower (0.10 TTO score points over 1 and 10.86 points over 100 in VAS score), obesity being the most influential risk factor.

Conclusions

The presence of established cardiovascular disease and/or cardiovascular risk factors, specially obesity, account for impaired quality of life in people with diabetes.

Associations Between Sleep Deprivation and Salivary Testosterone Levels in Male University Students: A Prospective Cohort Study

Sleep deprivation is a common health problem that is growing rapidly worldwide and it is associated with short- and long-term impacts on health. The aim of this study was to detect potential predictors of salivary testosterone (sT) association with sleep deprivation in Arab male university students. In this prospective cohort study, 77 university male students in the age range of 18 to 26 years were divided into two groups, sleep-deprived (SD) participants and non-sleep-deprived (NSD) participants. Sleep deprivation was defined as sleeping less than 5 hr per night. Blood samples and sT were collected from fasting participants to measure serum levels of glucose, lipid profile, leptin, serotonin, sT, and body mass index (BMI) values. The multiple linear correlation model of high-density lipoprotein cholesterol (HDL-C), BMI, and serotonin was positively correlated with sT (r = .977, p < .05) in the SD group. No correlations were identified with sT in the NSD group. In the SD study group, the multiple linear regression model of HDL-C, BMI, and serotonin was significantly influenced by sT (R² = .955, p < .05). These predictors together explained approximately 96% of the variance in sT levels in the SD study group. No predictive variables for sT were reported in the NSD group. Results indirectly confirmed the presence of a positive association between sT and sleep deprivation in young men. This association is mediated by three factors, HDL-C, BMI, and serum serotonin, which are collectively considered as part of a significant physiological adaptation to sleep deprivation in young men.

Imperfect information on physical activity and caloric intake

Using the National Health and Nutrition Examination Survey Data, I find that individuals who overestimate their activity level by one standard deviation consume 40-60 extra calories per day, or enough to gain five pounds per year. These extra calories are composed mainly of sugar and carbohydrate, and are concentrated among individuals in the 75th and 90th percentiles of caloric intake. The link between overeating and inaccurate estimation of physical activity is strongest among less educated individuals and individuals with high variance in their physical activity, suggesting that imperfect recall or information gaps explain at least part of the relationship of interest. These results imply the existence of a necessary condition for physical activity-based information treatments to be effective in changing health behaviors and obesity rates.

Cardiovascular risk factors-using repeated cross-sectional surveys to assess time trends in socioeconomic inequalities in neighbouring countries

OBJECTIVES

This study compares trends in socioeconomic inequalities related to key cardiovascular risk factors in neighbouring countries Northern Ireland (NI) and the Republic of Ireland (RoI).

DESIGN

Repeated cross-sectional studies.

SETTING

Population based.

PARTICIPANTS

3500-4000 in national surveys in NI and 5000-9000 in RoI, aged 20-69 years.

MEASURES

Educational attainment was used as a socioeconomic indicator by which the magnitude and direction of trends in inequalities for smoking, diabetes, obesity and physical inactivity in NI and RoI were examined between 1997/1998 and 2007/2011. Gender-specific relative and absolute inequalities were calculated using the Relative Index of Inequality (RII) and Slope Index of Inequality (SII) for both countries.

RESULTS

In both countries, the prevalence of diabetes and obesity increased whereas levels of smoking and physical inactivity decreased over time. In NI relative inequalities increased for obesity (RII 1.1 in males and 2.1 in females in 2010/2011) and smoking (RII 4.5 in males and 4.2 in females in 2010/2011) for both genders and absolute inequalities increased for all risk factors in men and increased for diabetes and obesity in women. In RoI greater inequality was observed in women, particularly for smoking (RII 2.8 in 2007) and obesity (RII 8.2 in 2002) and in men for diabetes (RII 3.2 in 2002).

CONCLUSIONS

Interventions to reduce inequalities in risk factors, particularly smoking, obesity and diabetes are encouraged across both countries.

Labor market consequences of childhood onset type 1 diabetes

This paper examines the effect of the onset of Type 1 Diabetes Mellitus (T1DM) before 15 years of age on labor market outcomes and contributes to the literature on effects of childhood health on adult socioeconomic status. Using national Swedish socioeconomic register data 1991-2010 for 2485 individuals born 1972-1978 with onset of T1DM in 1977-1993, we find that T1DM in childhood has a negative effect on labor market outcomes later in life. Part of the T1DM effect is channeled through occupational field which may be related to both choice and opportunities. Although the magnitude of the effect is only directly generalizable to illnesses with similar attributes as T1DM, the results suggest that causality in the often observed correlation between health and socioeconomic status, at least partly, is explained by an effect running from health to earnings. This has implications for research and policy on strategies to reduce socioeconomic-related health inequality. Our findings also shed light on productivity losses, measured by employment status and earnings due to childhood onset T1DM, which have implications for both the individual and society.